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1 STAKEHOLDER COMMUNIC ATION AND COLLABORAT ION IN THE DIGITAL A GE: HOW U.S. HIGHER EDUC ATIONAL INSTITUTIONS ENGAGE STAKEHOLDERS ON SOCIAL NETWORKING SI TES By YANQUN LOU A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERS ITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN MASS COMMUNICATION UNIVERSITY OF FLORIDA 2013
2 2013 Yanqun Lou
3 To my dearest parents for their love, support, and encouragement throughout my academic career
4 ACKNOWLEDGMENTS I would like to extend my heart felt thanks to a host of people without whose assistance the accomplishment of this thesis would have been impossible. First and foremost, I am deeply inde bted to my thesis committee led my Prof Juan Carlos Molleda who provide d all the necessary guidance during the process of thesis design and construction. H e has been a truly inspiring mentor and a close friend. I am also grateful to Dr Moon Lee and Dr K iousis Spiro without whose valuable instruction and kind support, it would be impossible for me to stretch this far in the pursuit of academic excellence. Beyond all this, I am most exceedingly obliged to my parents for their trust, consistent support an d encouragement all along the way
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 11 Social Media and Symmetrical Communication ................................ ...................... 11 Social N etworking S ites and C ollaborative N etworks ................................ ............. 12 International M arket of H igher E ducation ................................ ................................ 14 2 LITERATUR E REVIEW ................................ ................................ .......................... 18 Defining the C oncept: S ocial N etworking S ites (SNS) ................................ ............ 18 Contextualizing SNS C ommunication ................................ ................................ ..... 21 User S egmentation ................................ ................................ ........................... 21 SNS for G lobal C ommunication ................................ ................................ ........ 24 M odels of P ublic R elati ons and S ymmetrical C ommunication .............. 26 Dialogic T heory of P ublic R elations ................................ ................................ ........ 29 SNS for C ollaborative N etworking ................................ ................................ .......... 31 Collaborative N etworks, an E merging M ultidisciplinary C onstruct .................... 32 Collaborative N etworks in the D igital A ge ................................ ......................... 36 Power ................................ ................................ ................................ ......... 36 Knowledge ................................ ................................ ................................ 38 Emerging C ollaborative N etworks on SNSs ................................ ..................... 40 Summary and R esearch Q uestions ................................ ................................ ........ 44 SNS S takeholder E ngagement and Asymmetrical Strategies .......................... 45 Uni versity SNS Strategies ................................ ................................ ................ 46 Research Questions ................................ ................................ ......................... 48 3 METHODOLOGY ................................ ................................ ................................ ... 54 Population and Sampling ................................ ................................ ........................ 56 Instrument C onstruction ................................ ................................ .......................... 58 Data Collection and Analysis ................................ ................................ .................. 64 Intercoder Reliability ................................ ................................ ............................... 68 4 RESULTS ................................ ................................ ................................ ............... 71
6 Dissects of SNS C ommunication S ymmetry ................................ ........................... 71 The E merging D ynamic of SNS C ollaborative N etworking ................................ ..... 77 SNS S takeholder R esponse ................................ ................................ ................... 79 Cult ural D ifferences of SNS C ontents ................................ ................................ ..... 82 Summary ................................ ................................ ................................ ................ 84 5 DISCUSSION ................................ ................................ ................................ ......... 90 C ommunication S ymmetry on Facebook, Twitter, and Weibo ................................ 90 The D ynamic of SNS C ollaborative N etworking ................................ ...................... 93 Cultural D ifferences on U niversity SNSs ................................ ................................ 95 Implications for T heory and P ractice ................................ ................................ ....... 97 Limitations and S uggestions for F uture R esearch: ................................ ............... 100 APPENDIX A C ODEBOOK: SNS CONTENTS ................................ ................................ ........... 103 B CODE SHEET 1: FACEBOOK, TWITTER, AND WEIBO SITE ............................ 111 C CODE SHEET 2: FACEBOOK WALL POSTS; TWITTER TWEETS; AND WEIBO CONTENTS ................................ ................................ ............................. 116 LIST OF REFERENCES ................................ ................................ ............................. 118 BIOGRAPHICAL SKET CH ................................ ................................ .......................... 130
7 LIST OF TABLES Table page 2 1 s ix c ultural d imensions ................................ ................. 51 3 1 U.S. Universities, institution types, history of Facebook account, and ................................ .......... 58 3 2 cation strategy ................. 61 3 3 ................... 69 4 1 SNS communications strategy f requency d istribution ................................ ......... 74 4 2 Descriptive s tatistics: SNS c ommunication s ymmetry ................................ ........ 75 4 3 Descriptive statistics: SNS stakeholder r esponse ................................ ............... 80 4 4 Pearson correlations for Facebook CNV and stakeholder response value ......... 82
8 LIST OF FIGURES Figure page 4 1 Frequency distribution for Facebook communication strategy ............................ 86 4 2 Frequency distribution for Twitter communication strategy ................................ 86 4 3 Frequency distribution for Weibo communication strategy ................................ 87 4 4 Means of communication symmetry value on Twitter, Weibo, and Facebook. ... 87 4 5 Means of collaborative networking value on Twitter, Weibo, and Facebook. ..... 88 4 6 Means plot for SNS IDV value ................................ ................................ ............ 88 4 7 Means plot for SNS MAS value ................................ ................................ .......... 89 5 1 An example of uni versity social media dashboard ................................ ............ 102
9 Abstract of Thesis Presente d to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Arts in Mass Communication STAKEHOLDER COMMUNICATION AND COLLABORATION IN THE DIGITAL AGE: HOW U.S. HIGHER EDUCATI ONAL INSTITUTIONS ENGAGE STAKEHOLDERS ON SOCIAL NETWORKING SITES By Yanqun Lou August 2013 Chair: Juan Carlos Molleda Major: Mass Communication In recent years, more and more social interactions and business transactions are happening on the Internet an d among demographi cally diversified populations. Social networking sites (SNS) are now becoming a global sensation. Following the footsteps of large corporations, public institutions like universities and colleges have been well aware of the immense valu e of the new medium. T his research explores the concept of and stakeholder response dynamism, and compare the differences of SNS cultural orientations. As the evolution of web based communications enters the age have an urgent mandate to advance theo ries and models to reflect the changes. This early, exploratory research on SNS mediated public relations and strategic communications is only a small step to that end. T he theoretical underpinnings of this research are J. Grunig s model of public relati ons, Kent and Taylor s dialogic theory, the concept of collaborative networking, and Hofstede s model of multidimensional national
10 cultures. In terms of methodology, t h is research took the path of quantitative content analysis to examine features, content s and trends on university Facebook, Twitter, and Sina Weibo sites.
11 CHAPTER 1 INTRODUCTION Social Media and Symmetrical Communication An important objective of organizational strategic communication is to engage stakeholder groups through persuasive com munication or relationship cultivation. J. Grunig and Hunt (1984) elaborated on how organizations approach their strategic public via media and proposed a normative theory of excellent public relations, together with four communication models: press agent ry, public information, two way asymmetrical, and two way symmetrical (cited in J. Grunig, 1992). Development of the four models is essentially rooted in some critical presumptions about the social role of public relations in society and the power relatio ns between organizations and publics (Grunig, 1992). It asymmetrical communication tendency, whereas a desirable end of public relations should be symmetrical communication tha t honors system holism, interdependence, and moving equilibrium (Grunig, 1987). Increasingly, internet mediated communication allows stakeholders more opportunities to voice concerns, contribute resources, and control information fl ow. As a democratic and unstructured social media public sphere based on the Internet, social networking site ( SNS ) has transformed traditional ways of mass communication from elite gate keeping to a style of digital word of mouth communication among ordinary information consume rs, who talk to each other, aggregate social capital, and seek knowledge emerging from the Net to form personal relationships in Cyberspace (Laroche, Habibi, Richard, & Sankaranarayanan, 2012; Rheingold, 1993). In other words, the traditional one way comm unication format in
12 which organizations unidirectionally impose messages to their audiences through information exposure and reputational control no longer holds truth. Instead, mutual engagement and relational efforts via online social networking and mic roblogging gradually becomes the mainstay. Notably, applications and communication tools administrator and make it possible for more public surveillance of information authe nticity (Kiyoshi, 2009). Stakeholder communications on SNS, in this regard, are moving towards a higher degree of communication symmetry (Kowalik, 2011). Social N etworking S ites and C ollaborative N etworks The concept of collaboration is also relevant to t he current study. The communicative features of social media, including the diversity of information sources and viral message transmission (Mills, 2012), particularly pertains to the idea of collaborative networking. Camarinha Matos and Afsarmanesh (200 5) proposed that collaborative networks serve to create synergy among industrial partners at t he intra organizational level. Could the similar dynamic be happening interpersonally or between people and organizations on social netw orking sites? For the sus tainab le development of organizations educational institutions as a focus of the current study, stakeholder communication is an important aspect of external communication. By nature, social networking sites such as MySpace, Facebook, and Twitter are grou nded in relationship building and networking (Boyd & Ellison, 2007) between individuals who share offline connections, among complete strangers, or between organizations and individuals who are willing to become part of an online community. Useful content s generated by Internet users within an open content community through collaboration (Kaplan & Haenlein, 2010) can reinforce individual
13 friendships and community support. Streams of digital conversations can reinforce self efficacy sparkle social identit y expression, and formulate a sense of identification within collaborated online communities (Johnson, Bazaa, & Chen, 2011). A distinctive aspect of online social networking is its contribution to the shift of communicative power from organizations to end users. Emerging from this changing dynamic of relationships is a collaborative network integrating the strategic resources and social capital of the social media population Traditional perspectives on collaborative networks grow out of inter organizatio nal relationship collaboration (Parung & Bititci, 2008). Competitive advantages of a collaborate network within corporations can be achieved in four ways: 1) improving efficiency via reduction of transaction costs and reduced cycle times and time to marke t; 2) distribution of risks in asset investment and relationship building; 3) improving learning, through better knowledge exchange; and 4) creation of synergy through the combination of resources and capabilities (Mena & Humphries, 2008). Witnessing the rise of SNS based virtual community and social networks, scholars identif ied a similar collaborative symbiosis between social media users and corporations seeking extensive engagement with their stakeholder groups (Deuze, 2006; Anderson, 2010). Kaplan and Haenlein (2010) regarded collaborative projects as a crucial application of social media communication users and are, (p. 62). Joint efforts from multiple information sources create a constructive co production platform for content creation. An excellent example of social media based collaboration is the online encyclopedia Wikipedia (Kaplan & Haenlein, 2010), defined
14 Collaborative networks on social media platforms provide organizations with vast opport unities to improve stakeholder communication strategies and to facilitate an open, collaborative negotiation (Roper, 2005). The current study is interested in explicating the viability of collaborative networking among higher education institutions and th eir strategic publics and exploring the possibility of SNS mediated collaborative networking s in a cross cultural context. According to McAllister (2012), u niversities and colleges have a great interest in adopting the model of Web 2.0 communication to facilitate dialogues with current students and alumni, to engage with prospective students, and to turn them into loyal social media followers Kowalik (2011) suggested that social media p rovides institutions of higher education with vast opportunities to interact with prospective students, alumni, donors, and at large community members. Chances are that a more friendly and engaging facet of universities, as conveyed through their Facebook fronts for instance, can help humanize the stories of their students faculty, and alumni, which in turn, can create brand loyalty among followers and more business opportunities (e.g., recruiting prospective students) (Kowalik, 2011; Solis, 2008). Inter national M arket of H igher E ducation The rationale behind the use of Web 2.0 technologies by U. S institutions of higher education to reach more stakeholders can be fi nancial, as well as strategic. Stuck hard by the 2008 financial crisis, U.S. universities and colleges have been enduring a painful p eriod of financial stringency. In their examination of the financial
15 interiors of six New England colleges and universities, Center for Social Philanthropy and Tellus Institute (2010) pointed out that as a conse quence of investment failures in the financial sector, university annual budgets were slashed down; financial endowments were diminished due to investment losses; university staff faced lay offs, and the shrinking financial capability resulted in local bus iness downturns in college communities In 2008, most of U.S. institutions of higher education, public and private, wealthy or poor, felt the financial pinch. For instance, in 2009, major public universities, in alliance with other large education associ ations, published an open letter for U.S. President Barack Obama, arguing for more government spending on university education projects, facilities, and research (Wolinsky, 2009). enormous bailouts already paid to the banking and automobile industries could dry up universities are driven to explore new sources of income growth to balance the budget, notably through recruiting more international studen ts who usually pay full tuitions and fees, and spend rather generously on living expenses while slashing down budgets for marketing and recruitment Under those harsh financial circumstances, social media tools quickly became a popular communication too l for university public relations efforts for the sake of cost effectiveness. Based on interviews with a systematic sample of Admission Officers in all 50 U.S. states, researchers at the University of Massachusetts Dartmouth found that communication cost reductions were associated with using social media to recruit and investing in SNS technologies. Social media was believed to be the new game changer for University recruitment and communication strategies (Barnes & Lescault, 2012)
16 The United States of A merica, in fact, has long been a desirable destination of higher education among international students. As the largest economy and the one and only superpower of the world, the country has assumed an important position of servicing quality academic resou rces to the world of hanke ring scholars. According to a joint report published by the Washington based Institute of International Education (IIE) and the Academic Cooperation Association (ACA), the United States hosted 723,277 international students durin g the 2010 2011 academic year, with Chinese students accounting for 21.8 % of the total i nternational student population This makes China the leading place of origin for international students in the United States, followed by India (14.4%), South Kor ea (10.1%), and Canada (3.8%) ( Open doors report, 2011). According to a 2012 report from the Council of Graduate Schools, prospective Chinese students now take up half of all applications to U.S. graduate programs (Fischer, 2012). The robust Chinese demand f or U.S. higher education can be attributed to the ascendance of a well off Chinese middle class (White, 2011), favorable interest rates for foreign investment (Fischer, 2012), and the affinity with U.S. popular culture among Chinese adolescents (Fackler, 2 002). On Chinese Internet discussion forums, more and more people started to converse about the relatively high student visa issuance rate at the U.S. Embassy and consulates in recent years (White, 2011). To some extent, the feverish talk on the Internet of greater access to U.S. higher education also played a part in the dramatic increase of applications from prospective Chinese students to U.S. institutions of higher learning. A similar trend of robust academic applications to U.S. universities was al so found in India. In the 2011 fiscal year, applications from prospective Indian students to U.S. academic programs soared 20 %,
17 (Fischer, 2011) To investigate how U.S. universities employ online social networking services to engage stakeholders from do mestic and international markets a review of literature include s topics concerning the nature of SNS, theoretical models of public relations, communication symmetry or dialogic communication the concept of s.
18 CHAPTER 2 LITERATURE REVIEW De fining the C oncept: S ocial N etworking S ites (SNS) Studies on the nature of social networking started from an exploratory explanation for social interaction and interpersonal communication within a larger social structure (Scott, 1991). Social network theory or social network analysis (SNA) lends an interdisciplinary theoretical lens into the network individual dynamic that emphasizes the importance of collective identity, social interaction, and the cultural construct of network of individual nodes into a larger web of interdependency creates a social net 440). Online social networking, based on what is now commonly termed as social networking sites, encompasses various features from social communication concepts and relies heavily on the advancement of information technologies. Kaplan and Haenle in (2010) considered SNS as an essential application of social media, defined by Web 2.0 technologies and User Generated Content (UGC). Though similar in a normative sense, distinctions have to be made between social media and SNS. According to Kaplan an based applications that build on the ideological and technological foundations of Web 2.0, and virtual world o f social networks mirrors the structure of tribal society from time immemorial which relied on connectivity and relationship building among individuals for survival and community prosperity (Das & Sahoo, 2011). For public relations
19 strategists, the commun ity effects of online social networking on interpersonal communication and stakeholder engagement are potential areas for further theoretical exploration. To smooth the transition of social network studies from interpersonal connectivity and social interac tion to Web 2.0 social networking, we need to give clear cut definitions for such terms as social web, social software, and most importantly, social networking that facilita categorized into two distinctive subsets: 1) people focused and 2) activity focused. Activity focused social websites collect information from individual users to form a thematic stru cture on a specific website for a specific function, i.e., Flickr (photo sharing), Lavalife (dating), and YouTube (video sharing); people focused soci al websites essentially revolve around personal online profile construction and social interaction via use r driven personal contents (Keenan & Shiri, 2009) that form the foundat ion of online social networking in a real time sense. In fact, the people centric logic of Web 2.0 communication is a defining feature of SNS. One of the most cited definition for SNS provided by Boyd and Ellison (2007) based services that allow individuals to (1) construct a public or semi public profile within a bounded system, (2) articulate a list of other users with whom they share a conne ction, and (3) view and traverse their list of network. Social networking sites such as Facebook and MySpace are notably different
20 from early public discussion forums that have little amplifying user personality and hardly address the quest for community support, connection, and interactivity on the Web. Other definitions for SNS st rike a similar note. For instance, McKinsey, the emphasis on the educational and social value of SNS for individual users (cited in Stroud, 2007). The popularity of online social networking is arguably a result of the prevalence of Web 2.0 technologies. Van Zyl (2009) saw online social networking as a social phenomenon that is power ed by Web 2.0 technologies and consequently discovery of potential relationships and sho uld aid in the conversion of potential ties into generated contents and user define d rules for application (Boyd, 2006; Richter, Riemer, & Vom Brocke, 2011). Examples of social software also include Wikis, microblogging, and social bookmarking services (Richter, et al., 2011). In a study on Facebook community of an intermediate French course informed by situated learning theory, Mills (2011) found that SNSs can help individuals develop a virtual identity, facilitate mutual engagement, and enhance the effectiveness of relationship building and cultivation. There are even chances that ind ividual users can aggregate social capital through online social networking that reduces the social cost of communication and breaks off the limits of geographical boundaries (Ellison, Steinfield, & Lampe, 2007).
21 To lend a critical perspective on these SNS definitions, there seems to be an absence of structural analysis of SNS variables, such as the characteristics of user population, communication strategies on SNS, and different contexts in which SNS communication takes place, such as corporate social med ia marketing (Thackeray et al., 2012), knowledge management and e learning (Kane, Robinson Combre, & Berge, 2010), brand community management (Laroche et al., 2012), and global word of mouth distribution (Lukito & Chan, 2010). Contextualizing SNS C ommunica tion User S egmentation Social networking sites do not crop up overnight. The growth of SNS can be identified as a strategic tipping point of modern life that happened at the turning of a millennium: SixDegrees.com the first recognized SNS site merge until 1997; the transient success of Friendster and MySpace and the later rise of Facebook, by far the most popular social networking site in history (Boyd & Ellison, 2008) attested to the theory of innovation diffusion in the sense that the adoption rate of new technology applications depends on the motivation and efficiency of the wider user population. Towards a more systematic understanding of SNS culture, it seems imperative for researchers to find out what kinds of people would connect them selve s with the gigantic web. In her study of teenage frenzy towards social media, Boyd (2007) coined the term which is essentially mediated, and have four defining properties: persistence, searchability, replicability and invisibility of audience. Attracted to the asynchronous and anonymous features of SNS (Boyd, 2007), innovators and early adopters embraced SNS soon after the technology became available. Lorenzo Romero, Alarcon del Am, and Constantinides (2012) pointed out that there wa s a
22 certain degree of homogeneity among early adopters, however, as the diffusion continued, user segments and various motivations for adoption came into existence. Previous studies indicated that social media user segmentation may not be as closely assoc iated with socio economic, cultural or ethnic indicators as with other social phenomenon, but is more closely related to different types of motivation for SNS use, the degree of individual dedication to online social networks, and the dexterity of user dig ital skills (Lorenzo Romero et al., 2012; Sessler, 2009;). O n the one hand, Sessler (2009) classified user motivation into three categories: 1) real life conversations and interactions with businesses or individuals with whom they have developed various degrees of offline connection; 2) content creation, which is about the generation of contents on the public domain: the Internet and joint construction of meaningful contexts; and 3) administration that in volves strategic planning, goal specification and opti mization of digital resources. On the other hand, in their study on the typology of networked consumers in the Netherlands based on the frequency of user activity, user sociodemographic variables, soci al networking experience, and patterns of interaction, Lorenzo Romero et al. (2012) found that there are generally three types of users: introvert users, versatile users, and expert communicator users. Though the majority of users tends to rely on SNS s fo r information sourcing and message distribution, the group of expert communicator s s the most interesting possibility as a potential Moreover, users tend to aggregate technological expertise and digital media intelligence to get the best experience out of SNS use, at the same time as SNS develop more
23 user friendly features and widgets that help optimize the user experience of social media communication (Lorenzo Romero et al., 2012). User segmentation of SNS population has significant implications for public relations practitioners who try to devise more effective and tailored engagement strategies for a diversified user population on SNS. Among all the sub cultural seg ments of SNS user population, the youthful population or the Millennial Generation is of particular importance to the current study. Defined as young people born after 1981, the Millennial Generation were born into new technologies, confident of digital m edia use, in hope of better social connections (Taylor & Keeter, 2011), and were growing up as a witness to the wax and wane of several popular SNSs. From a psychological perspective, young people, especially teenagers, may develop reliance on SNS for the sake of identity formation and expression (Weber & Mitchell, 2008), as well as of constructing bounded social circle in which they can feel found several psychological facto rs that contribute to the youthful engagement with SNS: need for cognition and attention from peers, mood enhancement, social connection with information sources and psychological escapism. Weber and Mitchell (2008) noted that through digital production a nd consumption of media contents, in incorporati The overwhelming representation of youthful aspirations on SNS has great value for onlin e marketing and consumer relationship cultivation. Willett (2008) contended that consumer culture is flourishing on SNS; companies increasingly position young
24 consumers active on SNS as active participants in content production and resource sharing, as op posed to passive information seekers. Through their aggregate findings on e commerce information sharing among a sample of young people aged between 15 to 18, Jansen et al. (2011) found that though the youthful demographic have fragmented e commerce infor mation behavior, yet for those who have comprehensive SNS profiles or who tend to update SNS status frequently, there is a strong likelihood that they will engage with commercial information sharing activities for the corporate brand community they identif y with. In situations where young adults spend a huge amount of time and resource on information seeking and knowledge build up, SNS s can also provide opportunities for collaborative knowledge management (Kane et al., 2010). Kane et al. (2010) found that Web 2.0 social networking tools can facilitate knowledge management and e learning activities within an organization, through wiki based employee projects. For the sake of communication and relationship cultivation, organizations can take advantage of the desire of learning and knowledge sharing among young people, especially students who have inclinations of searching information online for academic purposes, coproducing contents and building virtual communities on top of the collaboration dynamic. SNS f or G lobal C ommunication Another important context for SNS communication that lacks scholarly attention is the globalization of online social networking (Lukito & Chan, 2010). The use of social media is becoming a global phenomenon and SNS, as an importan t application of social media to Internet mediated communication, has already transcended national and cultural boundaries. Facebook, the U.S based SNS does not stay as a national
26 Discussions on the application of SNS in a global context need to be built on a m ore systematic understanding of how different cultural values, norms, and philosophies concerning human communication affect digitalized social networking, end Ling, 2010). F or organizations operating communication activities in a broader geographical context, SNS provides opportunities for global strategy making that would help maintain the consistency of communication on a single platform that nevertheless, targets a cultura lly and linguistically diversified audience. However, Lukito and Chan (2010) pointed out that the flip side of globalized SNS communication could be crisis spilt over national boundaries much more easily and a viral spread of negative organizational reput ation through digital word of mouth. Plenty of research has been done to study global SNS communication strategies, such as those based on Facebook and Twitter, for corporate stakeholder engagement. However, there is a shortage of literature dealing with how educational institutions adopt this Web 2.0 innovation to engage strategic publics from overseas countries. Nor is there much literature that meaningful relationsh ip and productive collaboration with their target publics. J. s M odels of P ublic R elations and S ymmetrical C ommunication Organization public relationship has long been a topic of interest for public relations scholars. Childers (1989) found that t h ere existed an evolution of intrinsic presuppositions for organizational public relations : from manipulation o f public opinions and persuasi ve communication to a more symmetrical and ethical communication framework characterized by mutual understanding, i nterdependence, and equilibrium. These presuppositions that arguably guided the practice of organizational public
27 relations over the past few decades are reflected and summarized in J. models of public relations. There are two independent d imensions to J. models: one way versus two way communication and asymmetrical versus symmetrical communication ( J. Grunig & Hunt, 1984). T he concept of symmetrical communication holds particular relevance to the current study on SNS communications It im plies the shift of communicati ve power through open discourses among different participating entities, respect for mutual interest, and concerns for communication equality. J. Grunig (1987) underscored that the underlying assumption of asymmetrica l communication is that organizations take the dominant position of communication and decide what is good for S ymmetrical communication on the other hand, is based on assumptions that public interests and concerns should be internalized making and the power of communication should be evenly and widely distributed among all stakeholder groups. According to J. Grunig (1992), p ress agentry/publicity is the model of one way asymmetrical communication. Th is model describes communication behaviors that are more persuasion and/or manipulation oriented. Public relations programmes associated with this model have little or no regard f or truth, ethics and mutual equilibrium (Childers, 1989), thus do not repres ent a sym metrical model of communication Public information is a one way symmetrical model for public relations. With this model, information that organization s choose to disclose to publics is generally truthful and accurate ( J. Grunig, 1992). However J. Grunig (1992) later acknowledged
28 and reconceptualize the model as asymmetrical. The two aforementioned models th organizational objectives through purposeful one way disclosure and dissemination, depriving, to a varying degree, the public s power of information management ( J. Grunig, 1992). The power structure underlying these models is therefore more asymmetrica l than symmetrical. The third model describes communication behaviors that are two way asymmetrical. The underlying presupposition of this model is that organizations are good enough to make the final decision on top of public responses and properly engin eer public consent through open dialogues and interactivity ( J. Grunig, 1992). The last model describes communication behaviors that are two way and symmetrical. According to J. Grunig (1992), the symmetrical model underscores mutual understanding betwee n organizations and their publics. The overarching tenet to this model is mutuality, reciprocity, and excellent communication, rather than persuasion and manipulation of public opinions. The process of symmetrical information exchange allows the public a strategic position to challenge organizational power and some greater control over self disclosure ( J. Grunig, 1992). J. communication are largely normative and open to validity and reliab ility tests in different communication contexts. In the age of Web 2.0 technologies, organizational public relationships are increasingly multidimensional in terms of medium and communication strategy types Arguably, some traditions of organizational co mmunication are being revolutionized with the surge of social media use and the popularity of online social networking that accentuate the value of personal relationships and community
29 development. Having said that, J. Grunig (2009) pointed out that digit al media may provide dialogical, interactive, relational, and global properties, perfect as a medium for strategic management paradigm of public relations; however communicators may duplicate their old communication strategies on the new media platform, th erefore the activities and communication strategies on social media and SNSs in particular. Dialogic T heory of P ublic R elations Another relevant theory that informs t he study of SNS mediated strategic communication is the dialogic theory of public relations. The dialogic theory is rooted from symmetrical communication literature (Kent & Taylor, 2002) and represents a significant paradigm shift of public relations theo ry from persuasion and manipulation of public opinions to managing communications and negotiating relationships (Ledingham & Bruning, 2000). Theunissen & Wan Noordin (2012) suggested that the concept of dialogue in mainstream public relations discourse an d scholarship is closely linked to J. way symmetrical communication model that highlights the importance of discussion, discours e and dialogue (Leeper, 1996). According to Kent and Taylor (2002), the concept of dialogue reflects a communicatio three features acknowledgement are
30 vulnerable to manipulation ; and 2002) As suggested organization public relationship development is a democratic communication proce ss that involves public understanding of agreement on the rules of communication. The idealism of symmetrical communication can only be realized when the aforementioned dialogic principles are satisfied (Pearson, 1989) The dialogic theory of public relations has been widely applied to researches on internet mediated public relations and SNS communication. Kent a nd Taylor (1998) identified five principles that guided relationship building between organizations and public dialogic communication, McAllister Spooner (2009) found that organizations have yet to take full advantage of the interactive capacity of the Internet. A similar trend has been and Seltzer (2009) found that environmental advocacy groups fell short of cultivating their Facebook applications that may facilitate the dialogic dynamic; Waters, Burnett, and Lucas (2009) found that non profit organizations were underutilizing their Facebook sites as a communication platform for genuine dialogues with stakeholders; McAllister (2012) concluded that key stakeholders of w silenced via a media that is intended for open dialogues.
31 Most literature on SNS based dialogic communication studied the issue from anal yzed (McAllister Spooner, 2009). The current study, by contrast, intends to stra tegic publics on Facebook, Twitter, and Sina Weibo. SNS for C ollaborative N etworking Both J. ideal scenario in which the power and resources of communication are evenly distributed a mong organizations and their stakeholders. In a two way symmetrical and relational development situation, stakeholders may anticipate greater involvement with term development. Spicer (2007) pointed out that stakeholder communication can also be achieved through collaborative advocacy, which involves active participation of stakeholder groups in the organizational communicative process The current study intends to look at the concept of collaboration and monitor the emerging dynamic of collaborative networking on SNSs. A review of previous literature on collaboration, collaborative networking and SNS communication among corporate and non profit organizations informed the current study about SNS collaborative networking for higher edu mmunication with stakeholders and the creation of a working definition for SNS collaborative network ing : SNS collaborative networking is an open ended communicative process of information exchange, knowledge formation and j oint value creation among a leaderless, heterogeneous collective of information agents who can be anyone who follow and keep in contact with organizations, on one or more social networking sites, for a common or compatible communication purpose.
32 Collabor ative N etworks, an E merging M ultidisciplinary C onstruct Collaboration is fundamentally a defining feature of human society. The term has been widely referenced, researched, and conceptualized across a variety of scientific disciplines: communications; edu cation in terms of knowledge management (Aguado Bened, 2002; Chen & Wei, 2008; Naik, 2011); psychological consultation (Conwill, 2003; Ma, 1995); industrial engineering (Goldberg, 2007; He, 2009; Schuh, Sauer, & Doering, 2008); computer science (Devedzic, Devedzic & Radenkovic, 2012; Janev, Dudukovic, Jovanovic, & Vranes, 2009; Vin, Chen, Barzilai, 1993); tourism (Aas, Ladkin, & Fletcher, 2005), management and leadership studies (Heyman, 2011; Mola & Bauer, 2011; Ruohomaa & Kutvonen, 2010), and public rela tions (Leichty, 1997; Murray, 2010; (Khosrow to play int o a specific research context. the concept, including but not limited to joint value creation, shared knowledge, heterogeneity of participating entities, partnership formation, etc. For instance, Rosen sharing virtual or p collaborative activity is to create shared values among collaborative entities who materialize partnership and communication with intangible or tangible resources of their own contribution. that collaboration can happen both synchronously and asynchronously, and at multiple
33 platforms, with the help of computer technologies and Web 2.0 social networks. To some extent, collaborat ion can be the outcome of relationship management or a manifestation of social networks among loosely connected individual and organizational entities. In his crowdsourced definition for collaboration, Rao (2012) emphasized on ominally large, leaderless, temporary, partly voluntary, 4 ). In other words, collaboration happens groups community, but not subject to stru ctural restraints (Rao, 2012). nature of co group, gives rise to another important multid isciplinary concept: to Camarinha Matos and Afsarmanesh (2005), a collaborative network (CN) is constituted by a variety of entities (e.g., organizations and people) autonomous, achieve common or compatible goals, and whose interactions are supported by Despite the fact that a great number of research p rojects and empirical studies have contributed to the understanding of collaborative networks in various disciplines (Camarinha Matos & Afsarmanesh, 2005), the gravity of CN studies is on intra organizational communication, industrial partnership, and incr easingly collaboration powered by information and computer technologies (ICT). From an enterprise centric perspective, collaborative networks can be a facilitator for both internal and external communication, and are of strategic value for corporate
34 capita l (Camarinha Matos & Afsarmanesh, 2005). Within the corporate cultural context, manifestations or variants for CN (Camarinha Matos & Afsarmanesh, 2004) include: Virtual Enterprise (VE), Virtual Organization (VO), Dynamic Virtual Organization, Extended Ent erprise, VO Breeding Environment (VBE), professional virtual community (PVC), e Science, and (Collaborative) Virtual Laboratory (VL). CN variants such as organizational p artnership: an alliance of corporate entities based on common goals (Collaborative) Virtual Labor atory (VL) imply a paradigm shift to collaboration among term cooperation networks of individuals, who use com Matos & Afsarmanesh, 2005, p. 441). The objective for collaborative networking is thus placed on long term relationship cultiva tion and management of a community culture among resourceful individuals. From a public relations perspective, collaborative networking is essentially about relationship cultivation in the long run. Sorenson, Folker, and Brigham (2008) suggested that coll aborative networking can be conceptualized as a theoretical orientation for business strategy making, conflict management, and stakeholder engagement. The Collaborative Networking Orientation (CNO), according to Sorenson et al. (2008), builds on a feminin e approach to long term relationship management and
35 term orientation for stakeholder e ngagement, and a win win scenario in which all participating collaborative mindset, organizations need to reorient themselves to relationship cultivation with pote ntial and existing stakeholders, transforming from a control model that is corporate focused, regards stakeholders as a source of risk, and prioritizes communication strategies of monitoring, listening and telling, to a more collaborative model in which the stra tegies of engagement are inclusive, stakeholders are more of a source of opportunity, and the premium communication strategies include collaborating, partnering and learning (Sloan, 2009). Given that the role of collaboration and collaborative networked entities is widely recognized by academics across disciplines and that the body of empirical knowledge on different forms of collaborative networks has been accumulated over the years, Camarinha Matos & Afsarmanesh (2005) proposed the development of a new scientific by provid ing theoretical foundation and structural evaluative framework for future research, as well as provide insights for practical implantation of CN. Recent tren ds on CN researches tend to focus on the formation of collaborative networks supported by information and computer technologies (ICTs), in such areas as collaborative process improvement and knowledge communication within an organizational hierarchy (Kock, 1999), remote innovation (Rura Polley & Baker, 2002), and business engagement
36 through virtual community development (Laroche et al., 2012; Wellman, Salaff, Dimitrova, Garton, Gulia, & Haythornwaite, 1996; Zhang, Jansen, & Chowdhury, 2011). Collaborati ve N etworks in the D igital A ge I ncreasingly, collaborative networking is getting digitalized. With the advent of a more interactive digital sphere in the era of Web 2.0, individuals who have only limited resources and power in the past are now joining the col laborative decision making Within a large collaborative network, individual users of digital technologies are empowered to learn and achieve more easily through interactivity, socia lization, and shared knowledge Power In the information age, power that comes with collaboration and networking is now shifting towards a crowd of geographically distributed individuals capable of providing dots of useful information to a common agenda wi th private or public organizations. Pr ivate companies and public institutions are now able to build collaborative frameworks in which the power of a collective of individuals is brought into full play, with the help of information and computer technologies For instance, Rura Polley and Baker (2002) found that electronic collaboration facilitates collective learning in a milieu of shared organizational knowledge and remote innovation. In their research, LiveNet a prototype system, was developed to genera te locally bound, collaborative experience for individuals from different organizations. The result o f such collaborat ive remote networking is the creation of a common language, shared organizational knowledge and expertise, and the formation of an agent based structure that assist members to achieve personal goals (Rura Polley and Baker, 2002).
37 Booher & Innes (2002) found that three basic conditions precede the emergence of network power: 1) the diversity of network agents (including stakeholders, agencie s, and citizens); 2) a situation of interdependence for different agents; and 3) authentic dialogue, featuring accurate and trusted communication flow among the diversity of participants. Using the connectionist model of neural networks, Booher & Innes (2 002) found that information in a connectionist network is essentially distributed and & Inne s, 2002, p. 225). The decentralization of organizational power in collaborative networking may create not only organization individual synergy, but also an explosion of engagement and mass creativity. An example of such power decentralization would be crowdsourcing among online community members. According to Brabham (2008), crowdsourcing grows out of online collaboration for problem solving and represents a lies in the fact that diverse perspectives and heuristics of individual members of an the problem solving process for organizations (Brabham, 2012) Web 2.0 technologies, in particular, are changing the dynamic of crowdsourcing to Social media applications, such as social bookmarking, social rating, and social networking sites boosted t he power of crowd by allowing vast social participation among end users, through aggregation of word of a pp. 54 56.).
38 Knowledge Scholars al so examined the nature of knowledge formation and knowledge sharing through d igitalized collaborative networking The concept of knowledge reality in the digital sphere basically revolves around three defining features: information aggregation, knowledge sharing, and non linearity of knowledge reproduction. Firstly information is connected and aggregated o n the public web Cripe and Weckerle (2009b) pointed out that the typical loose connection among individual contributors of information refers to a kin d of practical existence on the web and creates contexts and meanings for online aggregation of knowledge. The web norm goes that end users formulate a meaningful web reality by contributing brokered, affective, and sometimes marketed information bits (Ar Through hyperlinks search indexes, tagging, commentary and social networking, information is aggregated to produce meanings and enhance the credibility of original source contributor (Cripe & Weckerle, 2009b). I n fact, the connection of information itself made possible through web technologies represents a new variation of knowledge management that is participatory and open ended (Sini, 2009). This is particularly true with the popularity of Web 2.0 technologies that transcended from message centric informa tion system, such as e mailing repository centric model of systems such as blogs and wikis (Sini, 2009), to an emerging socio technical culture of collaboration, in which information aggregation is beyond a ra ndom communicative activity, but an assumed right, mindset and norms (Cripe & Weckerle, 2009b) for voluntary knowledge workers on the web, publishing and aggregating informal information chunks to form their own knowledge realities (Matsch ke, Moskaliuk, & C ress, 2012).
39 For the aggregated information chunks to make sense, the Internet based knowledge workers need to move up on the intellectual ladder to frame useful information into sharable knowledge that is relevant to their connected others. According to Allen (2010), knowledge sharing is an intellectual action, rather than a upon it. Sha red knowledge in Web 2.0 communities, in particular, can be business transaction information in local markets (Craigslist), job opportunities provided by professional networks (LinkedIn), or the latest updates of personal life from friends and families (Fa cebook) (Allen, 2010), all of which requires collaboration of some sort among participating users to cement the network power. At the preliminary stage, unstructured contents may have limited relevance to users, but via knowledge sharing and reproduction, meanings come into existence. Due to its nature of massive public participation in knowledge transmission and reproduction, Web 2.0 content communities may suffer varying degrees of challenge to their legitimacy, including vandalism from random contribut ors, exclusivity of data, administrator credibility, etc (Allen, 2010). It is believed that certain control mechanism needs to be put in place to regulate the Another important feature of digitalized knowledge reality is the non linearity of knowledge reproduction. At the first glance, the explosion of information digits on the Internet disrupted the traditional model of mass communication through one way information dissemination. The intellectuals who used to be po sitioned at the top of a
40 contribution to knowledge production is random, unstructured and democratic (Han, 2010). The feedback mechanism of blogs, for instance, breaks down the lin ear discourse into blog contents and commentary: the abbreviated units of information and communication can conveniently satisfy users seeking relevant and tailored messages (Han, 2010). Social networking site is another non linear model of Web 2.0 commun ication. Instead of creating narratives, SNS relies on the sharing of connections between people in personal, profession al or casual contexts (Cripe and Weckerle, 2009a) to aggregate information in a spiral process of socialization, externalization, comb ination and internalization (Shang, Li, Wu, & Hou, 2011). In other words, Web 2.0 services have revamped the linear word of mouth model from narration to c onversation and collaboration. According to Shang et al (2011), Web 2.0 knowledge production and rep roduction hinges on four types of service models: Exchanger, Aggregator, Collaborator, and Liberator The former two types enhance form of blog and a Bulletin Board; the following two service models provide opportunities of knowledge internalization and coproduction of intellectual capital for knowledge based participants, via wikis, bookmarking, networking, etc. Emerging C ollaborative N etworks on SNSs Under varying conditions, interactivity, co creation of c ontents, and collaborative networking are also emerging on social networking sites, providing opportunities for corporate engagement with consumers (Gummerus, Liljander, Weman, & Pihlstrom, 2012), cementing brand loyalty through SNS community activities (L aroche et al, 2012), expanding the social influence of non profit organizations in a cost effective way (Waters et al, 2009), and facilitating collaborative teaching and learning in higher
41 education settings (Wankel, 2009). Siri (2009) once compared Web 2 .0 social networking to a two way electricity grid in which end users, no matter individuals or (p. 93); and the soc ial graph displayed in the user to user or user to organization connection represents the critical wiring infrastructure t Notably, these vast expanses of social graph map out user connections and profiles, and help decentralize the task of information aggregation to individual users, who are now enjoying greater power of control and navigation. The fragmentation of information streams on multiple SNS platforms, inter connectedness among SNS us ers, and the network interoperability (Siri, 2009) have led to a decentralized and distributed public information sphere where users now assume greater responsibility for content production and information aggregation. SNS also provides an explicit graph repository for everyone to see and use, through user profile, user online transaction details and other digital footprints. According to Siri (2009), certain SNS services such a s Facebook nurtured undirected and symmetrical relationships; whereas other S NS tive networking can be an effective way to operationalize their strategic communication and stakeholder engagement goals. In fact, there has been a good many manifestations of two way information flow, coproduction of contents, and stakeholder engagement, on such popular SNS as
42 Facebook and Twitter, which can be considered as the prototypes of collaborative networks in the digital sphere A widely researched social media collaboration prototype is online consumer and stakeholder communities for corporate b rands. Laroche et al. (2012) found that social media brand communities can make significant contributions to corporate relationship marketing and brand loyalty reinforcement. geographically bound unique technological features of social media, SNS in particular, including digital arc hiving of past contents, milestoning and documenting important events in the brand community and digital narration in the form of texts, images, audios and visuals, etc, c cultivating brand community resources on social media platforms lies in the fact that s of information sharing and move towards a more universal perception and meaning about the brand (Singh & Sonnenburg, 2012). The collaborative dynamic on social media between the brand and its supporters can also be tapped by corporations through collabo rative digital story telling with their consumers (Singh & Sonnenburg, The Evolution Spot project, Singh and Sonnenburg (2012) found that the use of a combination of social media platforms (YouTube, Facebook, b
43 potential customers wer and expectations for the brand. Both Facebook and Twitter are widely used for online collaborative networking among random users. Facebook in particular, is widely used by corporations for consumer community engagement. Parsons (2011) evaluated 70 global corporate ded that most of these corporations realized the value of consumer engagement and relationship cultivation on Facebook. The trend goes that more and more consumer created communities would replace marketer created communities in that the perceived extrins ic motives of profit exploitation by corporations reduce the enthusiasm and motivations for participation (Lee, Kim, & Kim, 2011). The phenomenon is not without reasons. C creation momentum on SNS sometimes hinges on their attribution of intrinsic motives of altruism, social identification motives, and community engagement intentions (Lee, Kim, & Kim, 2011); or on whether corporations provide significant entertainment and social benefits for such mutual engagement and collab oration (Gummerus et al., 2012). Twitter is another popular SNS for business engagement and collaboration. Jansen, Zhang, Sobel, and Chowdury (2009) suggested that Twitter provided a communicative platform for organizations to hear customer testimony and gave instant replies and feedbacks. Zhang, Jansen and Chowdury (2011) also conducted a follow up path analysis for business engagement on Twitter and concluded positively that
44 of mouth (WOM) communication on Twitter enhanced consumer en gagement with the branding process and generated a flow of conversations. Twitter followers are now coproducing values with corporations through consumer generated eWOM (Zhang et al. 2011). Communication tools on Twitter include one way message announcem hashtags, and hyperlinks (Lovejoy, Waters, Saxton, 2012). Effective use of these communication tools on Twitter can, on the one hand, help organizations to maintain dialogues with followe rs, generate relevant topics in the dialogic loop, and expand the communicative influence by relating to other information sources; on the other hand, via momentum for co llaboration, using retweets and hashtags (Lovejoy et al., 2012). Summary and R esearch Q uestions In recent years, h igher education institutions have an increasing interest in adopti ng social networking sites for stakeholder communication Previous research es suggested that the strategic use of SNS would contribute to positive institutional reputation (Gilpin, 2010) and lead to more effective organization stakeholder relationships (Waters et al., 2009). Universities and colleges, for instance, are similar t o large corporations when it comes to communicating and interacting with strategic publics. Kantanen (2012) pointed out that stakeholder interaction with higher education institutions revolved around identity negotiation and image management. Universitie s and colleges tend to control diffuse organizational images in the external environment through branding, priority negotiations with stakeholders (Kantanen, 2012) across multiple communication channels, and marketization of university academic resources ( McNeill, 2012), etc, to bridge the internal and external reflections upon its strategic existence in the society
45 and more importantly, generate productive financial outcomes from stak eholder engagement. Kowalik (2011) found that social media applications s uch as Facebook, Twitter and Youtube were widely adopted by universities in the United States, Australia, Canada and New Zealand, for the purpose of engaging alumni, prospective students and their parents. The advantages associated with SNS stakeholder en gagement include connections with younger alumni who may shun traditional fund raising approaches by universities, creating new venues for friendly conversations with prospective students who have application intentions, cost effective information subsidie s, such as via sending out Tweets to concerned followers (Kowalik, 2011). of social media provides a cost effective way to engage with prospective students and build a meaningful relationship that can increase the odds of a student m atriculating to (Lovejoy et al., 2012, p. 13). SNS S takeholder E ngagement and Asymmetrical Strategies stakeholder views on their relationship with an organization in a way that may contended, is the developmental exercises that intend to enhance mutual understanding of sustainability and push the limits of cognitive, moral and e motional development. Both Facebook and Twitter can be creative and promising channels for critical information dissemination, brand promotion and stakeholder communication. Depending on the specific technical features of each SNS, organizations usually ha ve several communic ation strategies for stakeholder en gagement. Based on an extensive content analysis of 275 randomly sampled Facebook pages of non profit
46 organizations, Waters et al. (2009) summarized that there were basically three communication strate gies for Facebook stakeholder relationship cultivation, including 1) disclosure, 2) information dissemination and 3) involvement. Disclosure originates from to increasing crises in the for profit, nonprofit, and government sectors (Waters et al., 2009, p. 103). Information dissemination, on the other hand, emphasizes on the usefulness of websites for stakeholders (Taylor, Kent, & White, 2001) Carrera, Chiu, Pratipwattan awong, Chienwattanasuk Ahmad, and Murphy (2008) exemplified some commonly used forms of information dissemination, which include adding hyperlinks to external news items about the organization; uploading photos, videos, or audio files contributed by the organization or its supporters to the site; and using message boards or discussion walls to post public announcements and answer questions. The third strategy involvement, in another word, interactivity, as Waters et al. (2009) argued, can exert crucial influence on strategic communication with stakeholders online. They suggested that providing a calendar of events or a list of opportunities for user participation with those events can facilitate the process of stakeholder involvement both online and of fline. These three communication strategies are manifestations of an asymmetrical communication model of public relations with little stakeholder control of the information flow and communication resources. University SNS Strategies A more symmetrical org anizational communication model prioritizes conversations and dialogues among a diversity of participating entities. J. Grunig, L. Grunig, and Dozier (2002) found that relationships of trust with different publics grew out of two way symmetrical communica tion in whi ch organizations usually take into consideration the
47 opinions and concerns from different stakeholders for policy design and identity Fac ebook as an interactive forum for dialogic communication with key stakeholders such as current students, prospective students, and international students. The study developed by Kent and Taylor in 2002: mutuality, propinquity, empathy, risk and commitment. The result showed that 85 percent of the sampled universities utilized their Facebook pages for one way communication and the dialogic function of Facebook stakeho lder engagement was not played into full strength (McAllister, 2012). Twitter is another rising SNS platform for student engagement. Despite its 140 character restriction, Twitter, the powerful microblog, was found a more effective channel to facilitate p ublic dialogues than Facebook (Ebner, Lienhardt, Rohs, & Meyer, However, previous lit communication strategies. On the one hand, Lovejoy et al. (2012) argued that though Twitter provided a wide range of communication tools, including public messages, retweets, hyperlinks, h ashtags, and multimedia files including TwitPic and TwitVid, organizations most frequently used Twitter for traditional information subsidies in the forms of sharing hyperlin ks and retweeting messages. L ittle evidence had been found that these communicati on tools were being used for interactivity and relationship building. On the other hand, Junco et al. (2011) stressed the positive influence of
48 Twitter communication on college student engagement and student faculty collaboration, which is an essential fe ature of relationship cultivation in a higher cultivation potential may be attributed to the absence of consistent and systematic S NS performance by various organizations. By analyzing tweets from six randomly selected corporate Twitter accounts in both the US and Australia, Burton and Soboleva (2011) found that Twitter had the interactive capabilities for customer relationship building, but it turned out that companies us ing Twitter for customer engagement failed to devise strategic communicative objectives and consistent SNS policies for their Twitter practices. Research Questions The increasing popularity of social networking sites for stakeholder communication and relat ionship cultivation has been widely acknowledged in the academia, but the existing literature has yet to conclude on the nature and typology of SNS stakeholder communication strategies, especially in terms of the degree of communication symmetry. In order performance on (a)symmetrical SNS communication strategies, the current study in tends to answer the following research question: RQ1 : What are the most frequently used stakeholder communication stra tegies for U.S. universities on Facebook, Twitter, and Sina Weibo? RQ3: Are there any significant difference between U.S. public and private universities SNS profile, communic ation strategies and trends? Given its potential to facilitate dialogic communication (McAllister, 2012), promote a collaborative branding process (Singh & Sonnenburg, 2012), and generate active
49 user/stakeholder participation in the process of content prod uction and value creation (Wankel, 2009), social media applications, such as Facebook, Twitter, Youtube, Wikis, etc, may also be used by organizations to create vibrant collaborati ve networks with different stakeholders. Rambe (2012) conducted a critical discourse analysis of communication by universities enhanced micro level (educator learner and learner peer) relations, knowledge coproduction and collaborative engagement. T he current study is interested at finding whether the similar collaborative momentum exists for university stakeholder interactivity on Facebook, Twitter, and Weibo respectively. Hence, t he following research question: RQ 4 : How do U.S. universities collab oratively network on their Facebook, Twitter, and Weibo sites? Notably, a great variety of stakeholder communication contents and collaborative networking activities has led to the development of a dynamic information exchange and aggregation platform on S NSs. Whether the SNS communication strategies may actually take effects in terms of attracting stakeholder attention and generating significant stakeholder response bestows further research. The current study, therefore, proposes the following research q uestion: RQ 5 : Would the use of stakeholder communication and collaborative networking strategies by U.S. universities on Facebook, Twitter, and Sina Weibo generate significant communicatio n responses from stakeholders? Similar to social interactions in th e real world, conversations and networking in the (p. 601), Arora (2012) proposed a five fold typology that revealed the cultural
50 dimensions of Web 2.0 sphere: utilitarian driven, aesthetic driven, context driven, play driven, and value driven. Considering that SNS can be operationalized as a global platform for relationship cultivati on, it is also imperative to study how cultural differences and Ling (2010) found that people from different national cultures had different priorities for SNS communicatio n. A survey with 489 respondents from three countries: China, Korea, and the United States showed that SNS users from China and Korea tended to seek expert advice for important decision making and emotional support. They considered the virtual contacts, greetings, and relational resources aggregated on SNS important for social capital aggregation in the real time. By contrast, SNS users from the United States placed great emphasis on information exchange and expression of opinions and were more actively building up personal and relational resource through content sharing than through initiating and maintaining soci al contacts (Ji et al., 2010). Like many cross cultural communication and cultural difference studies, differen ces in the cultural orientation of SNS contents and communication strategy can be model of multidimensional national cultures his analysis of some 116,000 surve y questionnaire responses from IBM employees based in 72 countries. At the beginning, the model constituted of four major dimensions of national culture: power distance, individualism collectivism, masculinity femininity, and uncertainty avoidance (Hofste de, 1991; Minkov & Hofstede, 2011). Two additional dimensions were later added to the original model: the long term vs. short term orientation dimension and most recently, the indulgence vs. restraint dimension
51 (Hofstede, 2011) (See Table 2 1). These cul tural dimensions have been proven effective tools to measure differences of national cultures, in terms of values, norms, objectives, etc, at a macro level, but were not designed to measure micro, individual or inter organizational differen ces (Minkov & Ho fstede, 2011). Table 2 1 Category Definition Power Distance (PDI) The degree to which the less powerful members of a society accept and expect that power is distributed unequally. Individuali sm V.S. col lectivism (IDV) Individualism: a preference for a loosely knit social framework Collectivism: a preference for a tightly knit framework in society. Masculinity V.S. femininity (MAS) Masculinity: a preference for achievement, heroism, assertiveness, and ma terial reward for success. Femininity: a preference for cooperation, modesty, caring for the weak and quality of life. Uncertainty avoidance (UAI) The degree to which the members of a society feel uncomfortable with uncertainty and ambiguity. Long term V .S. short term orientation (LTO) Long term orientation: a search for society virtue; truth is believed to depend on situation, context and time. Short term orientation: a strong concern with establishing the absolute truth; focus is on achieving quick resu lts. Indulgence V.S. r estraint (IVR) Indulgence: a society that allows relatively free gratification of basic and natural human drives related to enjoying life. Restraint: a society that suppresses gratification of needs and regulates it by means of stric t social norms. Note : Definitions are cited from The Hofstede Center website. Retrieved from : http://geert hofstede .com/dimensions.html on Jan 15 th 2013 Previous literature suggested that national cultural orientations calculated by Hof ld be indicators of SNS adoption rates among emerging countries (Jobs & Gilfoil, 2012), different expec tation for SNS function, as well as social values associated with online social capital (Ji et al., 2010). Jobs and Gilfoil (2012 ) explained that collectivism was positively correlated with the rapid adoption of
52 social networking and microblogging in BRIC S (Brazil, Russia, India, China, and South Africa) and Mexico; the potential of SNS pronounced in developing countries than in developed countries such as the U.S., most of Europe, and Australia. Ji, et al, (2010 ) found correlations between three cultural expectation and motivation for SNS use and s ocial capital development. Cultural differences can be observed by comparing us er profiles, structured contents, and social interaction across different SNS communication platforms. Yu et al. (2011) contrasted the formation of trending topics on Sina Weibo, the popular Chinese microblogging site with trending on Twitter Results i ndicated that the process and outcome of trending on these two sites represented different user experience in areas of trending topics, media formats and information sources The current study would further analyze the com municative features of Sina Weib o, through comparisons with popular western SNS s, including Facebook and Twitter, in areas of user profile, stakeholder communication strategies, collaborative value, and cultural orientations of SNS contents To investigate how the issue of cultural diffe rence is reflected in higher education site stakeholder engagement behaviors, the current study intends to answer the following research question: RQ 6 : Wha strategies on Facebook, Twitter, and Sina Weibo, in terms of H cultural dimensions? Notably, a huge amount of texts and data are being produced, exchanged, and archived on social netw orking sites. Take the example of Facebook, numerous wall posts and
53 tags formulate gigantic data archives for individual users, groups, and organizations. In fact, a great deal of insights can be inferred from the data clusters and streams, the comments, may make employment of the data to have a better understanding about the purchasing tendency of potential customers and size up market trends for product launches (McCorkindale, 20 10). With the application of Facebook Timeline in 2012, the SNS advanced to provide more intelligent database services, allowing individual users to track digital footprints along a linear time frame. The Timeline is said to have streamlined the data arc hiving function of Facebook, by denormalizing the data, making Such a vast amount of relatively unstructured inf ormation on Facebook and other social networking sites bestowed a rare opportunity, as well as challenge, for communication scholars, trying to make activities, out of the da ta entries. To explore the linguistic and social contexts of Facebook, Twitter, and Sina Weibo, the three representatives of SNSs in the current valid inferences from texts (Krippendorff, 2004, p.18). According to Krippendorff (2004), content analysis is an unobtrusive, context sensitive technique, capable of processing large volumes of unstructured matter. The met hod, therefore, can be an efficient technique to explore the communicative context of social media and extrapolate the trends and communication patterns among SNS users.
54 CHAPTER 3 METHODOLOGY The current study employed the method of quantitative content a Given the strength of the method in unobtrusive and systematic quantification of texts to meaningful numbers (Riffe, Lacy, & F ico, 1998, p. 31), content analysis can be an effective tool to extract meanings out of random cont ents on social networking sites while logical inferences can be made about the nature of messages and the relationship between the content producers and the messages. Social media represents a robust trend for university stakeholder communication, especially in the case of universities engaging prospective students. A national survey among high school students in the Netherlands indicated that social media, though compared to traditional communication channels (Constantinides & Zinck Stag no, 2011). However, the survey results failed to answer some more in depth questions, sharing and information seeking activities on SNS s prospect ive students; whether the institution student dialogues and social interaction on
55 SNSs contribute to the success of Such questions as these can be further explored with the method of content analysis. In fac t, quite a number of studies on social media communication relied on content analysis as the primary research method. Facebook profiles and wall posts were sometimes studied closely in contexts to shed insight on for instance, civic political involvement during a presidential election (Fernandes, Giurcanu, Bowers, & al., 2009). Despi te its 140 character restriction, Twitter provides rich resources for content analysis researches. On Twitter, original tweets may be the first dimension of content; contents reproduced and summarized via Twitter communication tools, such as retweets, has h tags and hyperlinks created another dimension which internalizes external resources and active dialogues between the content producer and followers (Lovejoy et al., 2012). A distinctive feature of SNS content analysis study is that a diversity of data, beyond texts, can be used as valid units of analysis. Waters et al. (2009) designed a 30 item coding instrument for NPO Facebook profile, which included not only texts, but also URL, logo, photos, video, and audio files as valid units of analysis. Massi ve contents produced on SNSs left clues for how individuals and organizations construct virtual identities and build up relational resources. Though fashioned in real time, contents on SNSs were largely left unattended, unstructured, and deprived of unifi ed meaning s as soon as the communicative trend died down. Therefore, it behooves of experts and scholars to make valid inferences from available texts and data
56 To investigate how U.S. universities use SNSs for stakeholder engagement, collaborative netwo rking, and cross cultural strategic communication, the current study took the path of quantitative content analysis to examine contents on university Facebook, Twitter, and Sina Weibo sites. Population and Sampling Social media harbors great potential for stakeholder communication and reputation management. Following the footsteps of large corporations, public institutions like universities and colleges have been well aware of the immense value of the new medium. By 2009, more than ninety five percent of U.S. college admissions offices had adopted at least one form of social media and engaged with information distribution across different digital platforms: blogs, university official websites, and social networking sites (Selwyn, 2012). The population of the current study is, therefore, universities and colleges from different parts of the United States, public or private that have a sizable population of international students and that employ multiple social networking sites for domestic and international stakeholder communication A sample of 18 universities was selected for this quantitative content analysis. Official social networking sites of each sampled university, including their Facebook, Twitter, and Sina Weibo sites became the units of analysis; SNS contents, including wall posts, tweets, and comments posted by universities and stakeholders during a selected time period were the targets of observation. Since the current research has a special interest in finding out how universities engage with p otential stakeholders, especially international students on SNSs, the selection of sample was firstly informed by two external lists:
57 1. Open Doors Report 2011/2012 top 25 leading institutions hosting international students 2. US News and World Report national u niversities with highest percentage of international students i n the 2011 2012 academic year Based on the number of enrolled international students on campus, the top sixty one universities were included in the initial sample, as they represented some of t he most popular U.S. higher education institutions in the international education market. These universities are either profit seeking private institutions with a reputation for elite education, or public institutions financially supported by state and fe deral governments. All of them are national universities geographically dispersed across the United States. the initial samples had active contacts and activities on SNSs; a nd most importantly, 4:30 7:30 p.m. on Jan 10 th the initial sample, 11 percent of the initial sample population. As they attracted significantly less visitors on Facebook than the others, these 11 universities we re not included in the final sample. communication activities with international students, particularly Chinese students on Sina Weibo, only those universities that have official We ibo accounts run by university marketing or admission staff were included in the fina l sample. Hence, a total of eighteen U.S. universities were included in the fina l sample (See Table 3 1). Some of the sampled universities adopted Facebook, Twitter, and Weibo at a relatively early stage of the innovation diffusion, while the others caught up with the trend at a later
58 date. Up to February 2013, sampled universities had a longer history of Facebook use ( M = 52.72, SD = 10.04) than Twitter ( M = 42.78, SD = 6.04) and Sina Weibo ( M = 11.44, SD = 6.64) Table 3 1. U.S. Universities, institution types, history of Facebook account, and Institution Institution Type History of FB (number of months) FB likes St anford University Private 63 482,469 University of Michigan Ann Arbor Public 63 470,340 Yale University Private 63 427,136 Ohio State University Main Campus Public 63 242,919 University of Miami Private 56 190,237 Arizona State University Public 54 148,645 University of California Berkeley Public 58 143,449 Duke University Private 56 122,352 University of Minnesota Twin Cities Public 44 112,405 University of Illinois Urbana Champaign Public 41 95,562 University of Southern California Priv ate 32 79,027 University of Notre Dame Private 44 72325 University of Iowa Public 50 63,508 Georgetown University Private 62 48,807 Northeastern University Private 35 31,319 Binghamton University SUNY Public 50 21,740 Stony Brook University SUNY Publ ic 52 18,823 University of Rochester Private 63 16,771 N=18 N ote : T official Facebook sites, as recorded between 4:30 and 7:30 p.m. on Jan 10 th 2013. History of Faceb ook was calculated by adding up the number of months during which a university account was functioning. The history of universities Facebook accounts can be viewed from the Facebook timeline bar. Instrument C onstruction An instrumental codebook was de veloped to analyze the stakeholder communication strategies, communication symmetry, stakeholder response,
59 Sina Weibo pages. Along with variables derived from previ ous research (Water et al, 2009), the researcher conducted a preliminary test on five universities, two of which from the sample list, the others randomly selected outside the sample list. The five e carefully reviewed, in order to determine which items to be included in t he coding instrument and how variables from previous researches should be modified to fit the current research objectives. These five universities for the preliminary review are Ca rnegie Mellon University, New York University, Bryant University, University of Southern California, and Northeastern Univer sity. To answer the first research question, university stakeholder communication strategies was measured by four variables: complet eness of SNS profile, information dissemination, involvement, and dialogue (See Table 3 2). The developme nt of variables for universi ty SNS communication strategies was informed by J. Grunig and for communication (1998). The four communication strategies reflect a continuum of represents the most symmetrical form of stakeholder communication. Specifically, the institutional information, from contact information, geogr aphical location, to admission stakeholder communication strategy that mainly aims at distributing news and updates in relations to the institution, was measured by u
60 tweets containing facts, statistics, and past event information, etc. This type of communication strategy was deliberately employed by universities to subsidize stakeholders with a constant flow of information in line create a sense of engagement on their SNSs and was measured by contents that should generate public interest in university related online and offline activities. An attention or visit time, universities may encourage users to visit other websites and embed links to external internet resources in a wall post or tweet. Moreover, universities may directly invite stakeholders in a wall past or tweet to participate in an event organized by the university or its affiliated organizations way, symmetrical communication model, and was supposed to capture the dynamic of information exchange between universities and their stakeholders on SNSs on Facebook, Twitter, and Weibo was reflected i n wall posts and tweets that originated from stakeholders and were subsequently ret weeted or shared by universities Dialogical communication was also manifested by wall posts and tweets ori gina ted from universities with a purpose of prompt ing conversations and responses from stakeholders. Apart from wall posts and tweets, the dialogic features of university SNSs were also looked at SNS dialogic features make it possible for systematic institu tional response and greater stakeholder control of information. These features included: contact information for the institution, an active message board, a place for stakeholder
61 recommendation of external information resources, the use of communication s ymbols, embedded applications that allow precise information harvest, dialogue in the comment section, etc. Table 3 2 m odels of p ublic r elations SNS c ommunic ation s trategy (variabl es) Measures Press agentry/ disclosure (a symmetrical ) Completeness of SNS profile Presence or absence of the information, links to external web resources, etc. Public information ( symmetrical ) Information d issemination; Involveme nt Presence or absence of news links, status updates, public messages, messages that generate conservation of visits, etc. Two way communication (symmetrical) Dialogue Presence or absence of tags by fans, retweets with comments added, conversations, SNS d ialogic features, etc Collaboration (symmetrical) Collaborative networking The degree of information source diversity; the degree of information aggregation Collaborative networking is another key construct in this research. The concept of collaboration way symmetrical communication model and the dialogic theory. The underlying objective of symmetrical communication is mutual understanding (Grunig, 1992) and the creation of trust among all stakeholders, which relies on relational development and community support (Spicer, 2007). Kent and Taylor (2002) stressed that collaboration among interactants of information defines mutuality and remains an important premise to dialogism. The second r esearch question specifically looks into this dimension of university SNS communication strategy. Previous literature suggested that collaboration exists where there is a diversity of information agents (Booher & Innes,
62 2002), where information is aggrega ted among connected others to enhance the credibility of original source contributor and the value of information (Cripe & Weckerle, dimensions: the diversity of information s ource and the degree of information aggregation. Quantitative data analysis should tell the extent of collaborative networking between universities and other information sources, including stakeholders on Facebook, Twitter, and Sina Weibo respectively. In order to find whether there is any significant statistical correlation between U.S. a detailed classification system was devised to analyze the value of replies, comments, and an y other responsive behaviors from university stakeholders on SNSs On Facebook, the number e a post was used as a numerical measure for the communicative value of a particular wall post. Likewise, the number of people w numerical measure of the communicative comments following Facebook wall posts and tweets on Twitter and Weibo were coded into four categories in terms of the attribute value: positive, neutral/mixed, negative, and no relevance. A positive comment included language or emoticon s that express particula r wall post or tweet; a positive comment was also an expression of affectionate emotions towards the particular university, such as from alumni, current students, or faculty, regardless of message content. A negative comment contained language or emoticon
63 issues, and events described in a particular wall post o r tweet. A negative comment could also be r favorable or unfavorable stakeholder attitudes, but contained factual statements, objective evaluations, or communication symbols, bereft of emotional values. Importan tly, coders made decisions on whether a comment was relevant to the original weet were coded as irrelevant. SNS accounts on Sina Weibo, the popular microblogging platform in China, and made comparisons between Facebook, Twitter, and Weibo, in terms of communication symmetry, coll dimensions: individualism vs. collectivism (IDV) and masculinity vs. femininity (MAS) were employed to measure cultural differences on SNSs. Individualism is essentially to do with the degree of interdependence a society maintains among its member s. China is a highly c ollectivist culture, scoring 20 out of 100 on the dimension of IDV, as opposed to 91 for the United States (G. Hofstede, & G. J. Hofstede, & Minkov, 2010 ). In a colle ctivistic culture, people tend to define their self Hofstede, & G. J. Hofstede, & Minkov, 2010 ). Culture conscious U. S. universities may heed to the group mentality of Chinese people and consequently designed and distributed SNS contents pertaining to the Chinese cultural mentality on Weibo. For the
64 informa tion on individual achievements or latest news of an individual associated with the university tweets that contained information on research groups, colleges, and organizations. For those SNS contents, of which the cultu calculations (China: 66; the United States: 62). A high score on this dimension means that the society values competition, achievement, and success; on the other end of spectrum quality of life, relationship management and caring for others are more valued in a feminine culture (G. Hofstede, & G. J. Hofstede, & Minkov, 2010 ). SNS missions, the achievements of university faculty, research teams, students, alumni, or or tw eets introducing significant stakeholder relations, campus activities, and varieties of student life. Achievement and competitiveness were indicators of masculinity; whereas quality of life and relationship cultivation were indicators of femininity (Hofst ede, 1991). Data Collection and Analysis recent 2 0 wall posts, tweets, together with the comments followed were coded. The time for data harvest dated back from Feb 15 th 2013, for Facebook, Twitter, and Sina Weibo. Data collected during this period covered
65 SNS communic ation activities right after the 2013 winter break, at the time of which a variety of information about admissions, back to school events, festivals, student life etc, were posted by the universities and shared among stakeholders. Due to the large volume of texts and features on these SNSs, t he process of data collection ceased when the limit of 20 posts was reached. A total of 540 wall posts were collected from sampled universities Facebook sites, 540 tweets from universities Twitter sites, and 540 twe ets from universities Weibo sites. I n all, 1080 SNS contents, together with university SNS site features and user comments, were analyzed. University SNS profiles were coded in terms of the degree of completeness. Given the number of items that appear i n the profile section of each SNS, a numerical scale of 10 was used to measure the completeness of university Facebook profile, 7 for twitter, and 8 for Weibo. The degree of SNS profile completeness was operationalized as a measure for the degree of infor mation disclosure by institutions. The independent variable: institution type (public or private) may affect the performance of SNS profile com pleteness hence developed into the first hypothesis of the study H1: Significant difference exists between the means of public and private U.S. variables: information dissemination, involvement, and dialogue. Posts and tweets collected from Face book, Twitter, and Sina Weibo fell into these three categories. Since the three communication strategies are varied from each other in terms of the degree of communication symmetry, they were coded along a numerical scale of 1 3 to reflect the as 3. Besides, the presence of each dialogic feature on SNS was coded as having
66 added symmetrical value to the site. For instance, the presence of contact information, an active message board, an advanced search bar, site navigation tools (such as Facebook timeline) was coded as 3 for communication symmetry value. SNS communication symmetry was measured by the aggregate value of strategy and dialogic feature. Two factors may h ave affected the degree of communication symmetry on SNSs: institution type and medium. The following hypotheses indicated a potential correlation between the variables: H2: Significant difference exists between the means of public and private U.S. univer H3: Significant difference exists between the means of Facebook, Twitter, and Weibo communication symmetry value. In terms of stakeholder response value, stakeholder comments following were coded into a numerical scale of 3, 2, 1, and 0. A positive comment equals 3 in value, neutral/mixed comment as 2, negative comment as 1, and irrelevant comment as 0. sites represented the overall value of stakeholder response. Hypothesis regarding communication strategies and stakeholder responsive behaviors on SNSs should shed insight on the potential correlation between the degree of SNS communication symmet ry and t he amount of responsive value generated by stakeholders. Hence, the following hypothesis: H4: There is a positive correlation between SNS communication symmetry and the amount of SNS stakeholder response value. Collaborative networking is a key construct for the current study. Variables that measured CN included: diversity of information source and degree of information aggregation. The degree of information source diversity was calculated along a
67 numerical scale of 12 (a total of 12 source categories we re identified) for the entire university site during the period of data collection; the degree of information aggregation was measured by the number of information aggregation tools used on the entire site. The aggregate value of source diversity and info rmation aggregation creates a numeric measure for the degree of SNS collaborative networking. The following hypotheses should shed insight on the correlation between the degree of collaborative networking and the total amount of stakeholder response value on SNSs. H5: Significant difference exists between the means of public and private U.S. H6: Significant difference exists between the means of Facebook, Twitter, and Weibo collaborative networking value. H 7: There is a positive correlation between the degree of collaborative networking and the amount of SNS stakeholder response value. The assumption is that the richness of information structure and a more democratic communicati ve climate in which a great va riety of information sources are referred to would lead to greater participation of SNS users in content distribution and more positive stakeholder evaluation of the institution. Correlation tests were conducted to see whether the proposed hypotheses stan d. Facebook, Twitter, and Chinese Sina Weibo, since the stakeholders they try to engage sm versus collectivism and masculinity versus femininity were developed into four content categories. Numerically, individualistic SNS contents had a value of 2 in the IDV category, while collectivistic SNS contents had a value of 1 in the same category; masculine SNS contents had a value of 2 in the MAS category, while feminine SNS
68 contents had a value of 1 in the same category. The aggregate value for contents in the IDV category represented the degree of individualism on a particular university SNS. L ikewise, the aggregate value for contents in the MAS category represented the degree of masculinity on a particular university SNS. Inter site cultural differences were compared through inferential statistical analysis. H8: Significant difference exists b etween the mean IDV value of Facebook, Twitter, and Weibo. H9: Significant difference exists between the mean MAS value of Facebook, Twitter, and Weibo. Intercoder Reliability The researcher cooperated with another coder to refine data language, specify co ding categories, and test intercoder reliability for the coding decisions. A Chinese graduate student from the College of Journalism and Communications at the University of Florida was recruited and trained for the intercoder reliability test. The assis tant coder was herself working on a web design project for UF international student recruitment and had both academic kno wledge and professional skills with social media communications. On Mar 5 th 2013, a comprehensive training session was held for the ass istant coder. At the beginning of the training session, the assistant coder was informed about the research objectives, research questions, and variables. During the training session, the researcher introduced to the assistant coder the basic structure o f university SNS contents and the location of measuring items for each variable on Facebook, Twitter, and Weibo. The researcher also provided a detailed explanation for the rationale behind the operationalization of concepts and coding category developmen t. After the training session, an intercoder reliability test was run to examine the internal reliability of
69 all variables and the objectivity of coding decisions made by the two coders. On Mar 6 th and 7 th 2013, the two coders separately coded the conten ts and sites in accordan ce with codebook instructions. Out of the eighteen university samples, six were randomly selected as a subsample for the intercoder reliability test. The subsample was then divided into three groups: SNSA, SNSB, and SNSC. For SNSA all of the university Facebook posts (N=40), comments, and site features were coded. Likewise, for SNSB, Twitter tweets (N=40), comments, and site features were coded; for SNSC, Weibo tweets (N=40), comments, and site features were coded. A total of 6 university SNSs and 120 SNS posts and tweets were coded, accounting for 11% of the entire sample. All of the eleven variables for the current study, including the ones measuring stakeholder communication strategy, stakeholder response, the concept of col laborative networking, SNS site features, and SNS cultural difference were included in the reliability test. Krippendo calculated as a statistical measure for inter coder agr eement. T he two coders achieved a relatively high leve l of agreement on all the variables coded, with the alpha coefficients above .80 (See Table 3 3) Table 3 3 Variables Location Alpha Stakeholder communication strategy Wall post & tweet Ordinal .8523 Numeric measure of stakeholder Wall post & tweet Interval 1.0000 Numeric measure of stakeholder Wall post & tweet Interval 1.0000 Stakeholder comment value Comment Interval .9966 SNS Individualism/Collectivism Wall post & tweet Ordinal .9578 SNS Masculinity/Femininity Wall post & tweet Ordinal .9217
70 Table 3 3 Con tinued. Variables Location Kr Alpha SNS history Site Interval 1.0000 SNS profile completeness Site Interval .8870 SNS dialogic features Site Interval .8429 Collective networking I: Diversity of information sources Site Interval .8263 Collective network ing II: Degree of information aggregation Site Interval .8415
71 CHAPTER 4 RESULTS A total of 1080 SNS content pieces, collected from 54 university official SNSs were analyzed with SPSS statistical analysis. Descriptive, inferential, and co rrelation tests were run in the hope of providing a quantitative description for the dynamic of SNS stakeholder communication, especially in the research context of communications for U.S. institutions of higher learning. As far as the current research is concerned, such dynamic of SNS stakeholder communication is reflected in four relevant concepts: SNS communication symmetry, collaborative networking, SNS stakeholder response mechanism, and cultural difference of SNS stakeholder communication. This chap ter presents the research findings from statistical analysis performed on variables and data derived from those four concepts. Dissects of SNS C ommunication S ymmetry RQ1: What are the most frequently used stakeholder communication strategies for U.S. unive rsities on Facebook, Twitter, and Sina Weibo? dialogic features. For SNS profile completeness, samp led universities had an average of 5.67 items (n = 10) in their Facebook profiles, an average of 4.06 items (n = 7) in their Twitter profiles, and an average of 3.56 (n = 7) items in their Weibo profiles. On Facebook, 33.3% sampled universities (n = 6) ha ve six items in their profiles, 22.2% (n = 4) have five items, another 22.2% (n = 4) have four items, and 16.7% (n = 3) have three items. The university that had the most complete Facebook profile was Northeastern University, which had nine items in its p rofile and home page, providing a detailed account of institution history, mission, general information, location, contact
72 information, links to other web resources, etc, to the site visitors. On Twitter, 38.9% sampled universities (n = 7) had four items in their profiles, 27.8% (n = 5) had five items, 22.2 % (n = 4) had three items, 5.6% (n = 1) had two items, and another 5.6% (n = 1) had six items. Georgetown University had the most complete Twitter profile, which contained six items. On Chinese Sina W eibo, 27.8% (n = 5) sampled universities had five items in their profiles, 16.7% (n = 3) had four items, 16.7% (n = 3) had three items, another 16.7% (n = 3) had one items, 5.6% (n = 1) had seven items, 5.6% (n = 1) had six items, 5.6% (n = 1) had two item s, and 5.6% (n = 1) had no item for profile. University of Illinois at Urbana Champaign had the most complete Weibo profile, which contained seven items. Regarding the completeness of SNS profile, which is an tegic information disclosure, the research hypothesized that public and private universities may have statistically different SNS profile completeness. H1: Significant difference exists between the means of public and private U.S. completeness. T tests were run to compare the means of SNS profile completeness for public and private U.S universities on Facebook, Twitter, and Weibo separately. On Facebook, private U.S universities ( M = 5.89, SD = 1.13) had a more complete SNS profil e than public ones ( M = 5.44, SD = 1.54). There was no statistically significant difference between means (p > 0.05), M = 0. 44, 95% CI [ 1.79, 0.90], t (16) = 0.699, p = 0.495. Therefore, in the case of Facebook, the alter native hypothesis was rejecte d. On Twitter, private U.S universities ( M = 4.11, SD = 1.17) had a more complete SNS profile than public ones ( M = 4.00, SD = 0.87). There was no statistically significant difference between means (p > 0.05), M = 0. 111, 95% CI [ 1.14, 0.92], t (16) = 0.229, p = 0.821.
73 Therefore, in the case of Twitter, the alternative hypothesis was also rejected. On Weibo, public U.S universities ( M = 3.78, SD = 1.99) had a more complete SNS profile than private ones ( M = 3.33, SD = 2.00). There was no statistical ly significant difference between means (p > 0.05), M = 0.44, 95% CI [ 1.55, 2.44], t (16) = 0.473, p = 0.643. Therefore, in the case of Weibo, the alternative hypothesis was rejected. Overall, hypothesis one that indicated statistically significant diff erence between the means of As to the question of which stakeholder communication strategy is most frequently used on Facebook, Twitter, and Weibo respectively, the research finds that 1 ). On Facebook, of the entire 360 wall 107) were 4 1 ); on Twitter, 75.3% 4 2 ); on Weibo, 72.5% (n = 261) w ere 4 3 )
74 Table 4 1 SNS communications s trategy f requency d istribution SNS name Frequency Percent Valid p ercent Cumulative p ercent Facebook In formation d issemination 230 63.9 63.9 63.9 Involvement 107 29.7 29.7 93.6 Dialogue 23 6.4 6.4 100.0 Total 360 100.0 100.0 Twitter I nformation dissemination 271 75.3 75.3 75.3 I nvolvement 48 13.3 13.3 88.6 D ialogue 41 11.4 11.4 100.0 Total 36 0 100.0 100.0 Weibo I nformation dissemination 261 72.5 72.5 72.5 I nvolvement 76 21.1 21.1 93.6 D ialogue 23 6.4 6.4 100.0 Total 360 100.0 100.0 In terms of the number of di alogic features on each SNS, this research finds that U.S universities h ad more dialogic features on their official Weibo site ( M = 3.89, SD = 1.53) than Facebook ( M = 3.67, SD = 1.28) and Twitter ( M = 2.22, SD = 0.43). On Facebook, 38.9% (n = 7) of the samples had four dialogic features, 27.8% (n = 5) had five dialogic featu res, 16.7% (n = 3) had three dialogic features, 11.1% (n = 2) had one feature, and 5.6% (n = 1) had two dialogic features; on Twitter, 77.8% (n = 14) of the samples had two dialogic features and 22.2 % (n = 4) had three features; on Weibo, 38.9% (n = 7) of the samples had five dialogic features, 22,2% (n = 4) had three dialogic features, 16.7% (n = 3) had two dialogic features, 11.1% (n = 2) had six dialogic features, 5.6% (n = 1) had four dialogic features, and another 5.6% (n = 1) had one dialogic feature
75 RQ3: Are there any significant difference between U.S. public and private universities SNS profile, communication strategies and trends? SNS communication symmetry is an aggre gate numeric measure of values for SNS stakeholder communication strategy and the number of SNS dialogic feature s This Facebook, Twitter and Weibo sites. Descriptive analysis showed that university Facebook sites ( M = 39.61, SD = 4.69), on average, had a higher communication symmetry value than Weibo ( M = 37.83, SD = 8.54) and Twitter ( M = 34.17, SD = 6.28) (See Table 4 2 ). Of all the 18 samples, University of California Ber keley and Duke University had the highest communication symmetry value of 48 on Facebook; Arizona State University had the highest communication symmetry value of 53 on Twitter; University of Rochester had the highest communication symmetry value of 50 on Weibo. Table 4 2 Descriptive s tatistics: SNS c ommunication s ymmetry N Minimum Maximum Mean Std. d eviation Facebook c ommunication s ymmetry 18 28 48 39.61 4.692 Twitter c ommunication s ymmetry 18 28 53 34.17 6.280 Weibo c ommunication s ymmetry 18 23 52 3 7.83 8.535 Valid N (listwise) 18 symmetry: institution type and SNS medium were tested with the following two hypotheses.
76 H2: Significant difference exists between the means of public and private U.S. H3: Significant difference exists between the means of Facebook, Twitter, and Weibo communication symmetry value. T tests were run to compare the means of SNS communication symmetry for public and private U.S universities on Facebook, Twitter, and Weibo separately. On Facebook, public U.S universities ( M = 40.33, SD = 3.39) had a higher communication symmetry value than the private ones ( M = 38.89, SD = 5.84). There was n o statistically significant difference between means (p > 0.05), M = 1.444, 95% CI [ 3.33, 6.22], t (16) = 0.642, p = 0.530. On Twitter, public U.S universities ( M = 35.78, SD = 7.03) had a higher communication symmetry value than the private ones ( M = 32 .56, SD = 5.34). There was no statistically significant difference between means (p > 0.05), M = 3.222, 95% CI [ 3.02, 9.46], t (16) = 1.095 p = 0.290. On Weibo, private U.S universities ( M = 38.67, SD =7.98) had a higher communication symmetry value th an the public ones ( M = 37.00, SD = 9.46). There was no statistically significant difference between means (p > 0.05), M = 1.667, 95% CI [ 10.414, 7.081], t (16) = 0.404, p = 0.692. For all three SNSs tested, the alternative hypothesis was rejected. T herefore, hypothesis two that SNS communication symmetry was not supported. A one way ANOVA test was run to compare the means of SNS communication symmetry value betw een Facebook, Twitter, and Weibo (See Figure 4 4 ). The results showed that homogeneity of variances was violated, as assessed by Levene's Test of Homogeneity of Variance ( p < 0.05). Communication symmetry value (CSV) was statistically significantly diff erent between different SNSs, Welch's F (2, 32.258) = 4.256, p < .05. CSV on Twitter (M = 34.17, SD = 6.28) was less than that on Weibo (M =
77 37.83, SD = 8.54), and Facebook (M = 39.61, SD = 4.69), in that order. Games Howell post hoc analysis revealed th at the mean difference between the Twitter group and the Facebook group (5.444, 95% CI [0.90, 9.99]) was statically significant (p = .016). Since there was a statistically significant difference between means ( p < .05), the null hypothesis was rejected an d the alternative hypothesis was supported. The results indicated that hypothesis three was supported The E merging D ynamic of SNS C ollaborative N etworking An important objective of this research is to find whether the dynamic of collaborative networking is vibrant on social networking sites. Particularly, the research intends to answer the question of how different U.S universities employ their collaborative networking resources on multiple SNS platforms. The concept of SNS collaborative networking was operationalized into two continuous variables: diversity of information source and the degree of information aggregation. Collaborative networking value (CNV) was calculated by adding up the numbers of information sources referred to and information aggre gation tools used on a particular university SNS. RQ 4 : How do U.S. universities collaboratively network on their Facebook, Twitter, and Weibo sites? Frequency analysis showed that 77.8% (n = 14) of sampled universities had five information sources or less on Facebook, 11.1 % (n = 2) had six information sources, and another 11.1 % (n = 2) had seven information sources. On Twitter, 83.4% (n = 15) universities had six to eight information sources, 11.1% (n = 2) had nine information sources, and 5.6% (n = 1) h ad five information sources. On Weibo, 33.3% sampled universities (n = 6) had three different information sources, 22.2% (n = 4) had six information sources, 11.1% (n = 2) had seven information sources, 11.1% (n = 2) had
78 five information sources, 11.1% (n = 2) had four information sources, 5.6% (n = 1) had eight information sources, and another 5.6% (n = 1) had only one information source. In terms of the number of information aggregation tools used on each SNS, 61.1% (n = 11) sampled universities have us ed four information aggregation tools, 27.8% (n = 5) have used three tools, 5.6% (n = 1) had two tools, and another 5.6% (n=1) had five tools. On Twitter, 83.3% (n=15) universities had five to seven information aggregation tools and 16.7% (n = 3) had eigh t tools. On Weibo, 77.8% (n = 14) sampled universities had four or five information aggregation tools, 11.1% (n = 2) had three tools, 5.6 % (n = 1) had one tool, and another 5.6 % (n = 1) had six tools. ve networking efforts on SNSs was assessed using the value of collaborative networking. Public and private U.S universities may have different collaborative networking performance on SNSs and te to site. H5: Significant difference exists between the means of public and private U.S. A t test was run to compare the means of collaborative networking value (CNV) for public and private U.S universiti es on Facebook, Twitter, and Weibo. On Facebook, private U.S universities ( M = 8.67, SD = 1.41) had a higher CNV than the public ones ( M = 8.11, SD = 1.83). There was no statistically significant difference between means (p > 0.05), M = 0.556, 95% CI [ 2.19, 1.08], t (16) = 0.720, p = 0.482. On Twitter, public U.S universities ( M = 14.00, SD = 1.80) had a higher CNV than the private ones ( M = 13.22, SD = 1.92). There was no statistically significant difference between means (p > 0.05), M = 0.778, 95% CI [ 1.08, 2.64], t (16) = 0.885, p = 0.389. On Weibo, private U.S universities ( M = 9.22, SD = 2.11) had a higher CNV than the public ones ( M =
79 8.67, SD = 2.69). There was no statistically significant difference between means (p > 0.05), M = 0.556, 95% CI [ 2.97, 1.86], t (16) = 0.487, p = 0.633. Therefore, the alternative hypothesis was rejected and hypothesis five was not supported. H6: Significant difference exists between the means of Facebook, Twitter, and Weibo collaborative networking value. A one way ANOVA test was run to compare the means of SNS collaborative networking value for Facebook, Twitt er, and Weibo (See Figure 4 5 ). The results showed that there was homogeneity of variances, as assessed by Levene's Test of Homogeneity of Variance ( p = 0.061) and the means of CNV was statistically different between SNSs, F (2, 51) = 38.237, p 2 = 0.58. CNV score increased from the Facebook group ( M = 8.39, SD = 1.61) to the Weibo group ( M = 8.94, SD = 2.36), and the Twitter group ( M = 13.61, SD = 0.44), in that order. Tukey post hoc analysis revealed that the mean increase from Face book to Twitter (5.22, 95% CI [3.64, 6.81]) was statistically significant ( p < .0005), as well as the increase from Weibo to Twit ter (4.67, 95% CI [3.08, 6.25], p < .0005). Since there was a statistically significant difference between means ( p < .05), the null hypothesis was rejected and the alternative hypothesis was accepted. The results also indicated that hypothesis six was supported. SNS S takeholder R esponse Another important objective of this research is to find whether SNS stakeholder communication and collaborative networking is somehow correlated with significant stakeholder response to institution messages
80 RQ 5 : Would the use of stakeholder communication and collaborative networking strategies by U.S. universities on Facebook, Twitter, and Sina W eibo generate significant communication responses from stakeholders? In this research, SNS stakeholder response is operationalized in two kinds of varia bles: numbers and comments. S haring information on SNS s was measured by the te value of stakeholder comment is another important measure of SNS stakeholder response, indicating the overall stakeholder opinion of a particular institution message. Descr iptive statistics (See Table 4 3 ) showed that Facebook generated more sharing responses from stakeholders ( M = 1070.06, S D = 1214.70) than Twitter ( M = 118.83, SD = 77.15) and Weibo ( M = 561.67, SD = 1840.59); more stakeholders expressed M = 7675.61, SD = 8094.36) M = 48.44, SD = 34.33); stakeholder comment value is higher on Facebook ( M = 786.89, SD = 7.71) than on Weibo ( M = 169.22, SD = 145.69) and Twitter ( M = 20.39, SD = 13.82). Table 4 3 Descriptive statistics : SNS s takeholder r esponse N Minimum Maximum Mean St d. Deviation Facebook "shares" 18 124 4532 1070.06 1214.704 Twitter "retweets" 18 21 290 118.83 77.149 Weibo "retweets" 18 11 7924 561.67 1840.592 Facebook "likes" 18 1495 29488 7675.61 8094.359 Twitter "favorites" 18 9 156 48.44 34.326 Facebook comm ents 18 197 3106 786.89 727.706 Twitter comments 18 7 60 20.39 13.819 Weibo comments 18 7 484 169.22 145.690 Valid N (listwise) 18
81 The relationship between SNS communication symmetry and stakeholder response is illustrated in hypothesis f our and the relationship between SNS collaborative networking and stakeholder response is illustrated in hypothesis seven: H4: There is a positive correlation between SNS communication symmetry and the amount of SNS stakeholder response value. Pearson corr elation tests were run to test whether there is statistically significant correlation between SNS communication symmetry and stakeholder response value. Statistics showed that there was no statistically significant correlation between the number of Facebo communication symmetry (p > 0.05). On Twitter, there was no statistically significant value of SNS communicat ion symmetry (p > 0.05). On Weibo, there was no statistically value of SNS communication symmetry (p > 0.05). As indicated in the preliminary analysis, the relationship between SNS communication symmetry and stakeholder response value on Facebook, Twitter, and Weibo was not linear. Therefore, hypothesis four was rejected. H7: There is a positive correlation between the degree of SNS collaborative networking and the amou nt of SNS stakeholder response value. Pearson correlation tests were run to assess the relationship between the value of collaborative networking (CNV) and stakeholder response on Facebook, Twitter, and Weibo. Statistics showed that there was a strong pos itive correlation between CNV and t r (16) = .606, p = 0.008, with Facebook CNV explaining 37% of the variation in the n
82 There was also a strong positive correlation between CNV and the number of r (16) = .514, p = 0.029, with Facebook CNV explaining 26% of the found between CNV and Facebook comment value, r (16) = .440, p = 0.048, with Facebook CNV explaining 19% of the variation in Facebook comment value. Preliminary analysis showed that the relationships between Twitter CNV and the linear; neither were the relationships betw comment value. Since there was a statistically significant positive correlation between CNV and stakeholder response value on Facebook (See Table 4 4 ), hypothesis seven was partially supported. Table 4 4 Pearson correlations for Facebook CNV and stakeholder response value Facebook comment value Facebook CNV .606 ** .514 .440 Note. CNV = Collaborative Networking Value, = statistically significant at p < .05 leve l. Cultural D ifferences of SNS C ontents Cultural differences in SNS contents are expected across Facebook, Twitter, and collectivism) and MAS (masculinity versus femininity) were de veloped into two continuous variables in the current research, measuring the cultural orientations of SNS contents.
83 RQ 6 : on Facebook and Twitter and those on Sina Weibo in terms of cultural dimensions? The current research hypothesized that the mean value of SNS IDV and MAS are different across Facebook, Twitter, and Weibo Hence the following hypotheses: H8: Significant difference exists between the mean IDV value of Fa cebook, Twitter, and Weibo. One way ANOVA test was run to compare the mean value of IDV across Facebook, Twitter, and Weibo. There was homogeneity of variances, as assessed by Levene's Test of Homogeneity of Variance ( p = .502). Statistics showed that IDV score was not statistically significantly different between different SNSs, F (2, 51) = 2.406, p > 0.05. Therefore, the alternative hypothesis was rejected and there was no statistically significant difference between the mean IDV value across Facebook, T witter, and Weibo (See Figure 4 6 ). H9: Significant difference exists between the mean MAS value of Facebook, Twitter, and Weibo. One way ANOVA test was also run to compare the mean value of MAS across Facebook, Twitter, and Weibo. There was homogeneity of variances, as assessed by Levene's Test of Homogeneity of Variance ( p = .364). MAS score was statistically significantly different between different SNSs, F (2, 51) = 3.586, p 2 = 0.09. MAS score increased from the Weibo group ( M = 27.00, SD = 3.96) to the Twitter group ( M = 28.44, SD = 3.54), and Facebook group ( M = 31.00, SD = 5.80), in that order. Tukey post hoc analysis revealed that the mean increase from Weibo to Facebook (4.00, 95% CI [0.35, 7.65]) was statistically significant ( p = .029). Since there was a statistically significant difference between means ( p < .05) (See Figure 4 7 ), the null
84 hypothesis was rejected and the alternative hypothesis was supported Hence, hypothesis nine was supported. Summary communication strategies and answered the research questions regarding the dynamics of SNS communication symmetry, collaborati ve networking, and SNS cultural differences. Importantly, statistical analysis showed that public and private U.S. universities did not differ greatly from each other in terms of the completeness of SNS profile, SNS communication symmetry, and SNS collabo rative networking. Regarding the degree of SNS communication symmetry and collaborative networking, significant statistical differences were found across Facebook, Twitter, and Weibo. Culturally, according to statistics, the value of IDV did not vary from site to site, however the value of MAS did vary across Facebook, Twitter, and Weibo. Statistical tests were also run to test the potential correlations between SNS communication symmetry and stakeholder response, as well as between collaborative networki ng and stakeholder response. The result showed that there was statistically significant correlation between the degree of collaborative networking and the amount of stakeholder response on Facebook. Around the middle of February 2013, 1080 wall posts and tweets from 54 official university SNSs were collected and subsequently analyzed. Nine hypotheses were tested and the following is a recapitulation of the results.
85 H1: Significant difference exists between the means of public and private U.S. universitie H2: Significant difference exists between the means of public and private U.S. H3: Significant difference exists between the means of Facebook, Twitter, and Weibo communication symmetry value. (Supported) H4: There is a positive correlation between SNS communication symmetry and the amount of SNS stakeholder response value. (Rejected) H5: Significant difference exists between the means of public and private U. S. H6: Significant difference exists between the means of Facebook, Twitter, and Weibo collaborative networking value. (Supported) H7: There is a positive correlation between the degree of SNS co llaborative networking and the amount of SNS stakeholder response value. (Partially supported) H8: Significant difference exists between the mean IDV value of Facebook, Twitter, and Weibo. (Rejected) H9: Significant difference exists between the mean MAS v alue of Facebook, Twitter, and Weibo. (Supported)
86 Figure 4 1. Frequency distribution for Facebook communication strategy Figure 4 2. Frequency distribution for Twitter communication strategy
87 Figure 4 3. Frequency distribution for Weibo communication strategy Figure 4 4 Means of communication symmetry value on Twitter, Weibo, and Facebook.
88 Figure 4 5. Means of collaborative networking value on Twitter, Weibo, and Facebook. Figure 4 6. Means plot for SNS IDV value
89 Figure 4 7. Means plot for SNS MAS value
90 CHAPTER 5 DISCUSSION Communication S ymmetry on Facebook, Twitter, and Weibo According to J. Grunig and Hunt (1984), the underlying objective of the two way symmetrical model of public relations is to facilitate mutual understanding and manage relationships. Critics once pointed that, symmetrical communication represents a (Grunig, 1992); whereas in reality, few organizations would willingly forego their power of coordination and control over the communication privileges and purely serve the interests of their strategic publics (Childers, 1989). One of the objectives of this research is to explore the dynamics of communication symmetry on social networking sit es, to see whether SNSs are more mutually engaging and symmetrica l venues for public relations. Though slightly different from each other in terms of site structures and interactive features, Facebook, Twitter, and Weibo are believed to share similar commu nication objectives and information patterns. Statistical analysis of wall posts and tweets posted by sampled U.S. universities on the three sites indicated that institutional control of message contents and information flow remains strong on all three SN Ss. Educational institutions such as in the case of public and private U.S. universities still tried to linger on with the traditional stakeholder communication models by subsidizing their followers with institutional messages and gave relatively little s pace for open ended dialogues and mutual engagement with their strategic publics. The results also indicated that public and private U.S universities tend to use similar SNS communication and collaborative networking strategies. With equal amount of inve stment on SNS
91 stakeholder communication, both public and private universities are able to reach a wider domestic and international audience. In a sense, SNSs provide education institutions with a level playing field to compete for prospective students and build up institutional reputation. In terms of SNS communication strategies, r ather than promoting mutual engagement and dialogues U.S. universities seemed to have knitted a tangled information web of multiple SNSs, onto which the connections they mainta ined with followers were turned into tailored communication channels for more effective information dissemination. In many regards, Facebook, Twitter, and Weibo are more like interactive news websites, fluctuated with athletic news, university announcemen ts, information about school events, etc. For instance, on the official Facebook page of University of Miami, seven out of twenty wall posts coded were news or announcements institutional achievements, either attributed to university faculties or research facilities. Moreover, some of the SNS contents on Facebook were overlapped with those on s out during the same time period. Some of the wall posts and tweets even contained the same descriptive texts, pictures, and videos. Although, the results showed that S NSs provided yet another platform for information subsidizing and brand management for U.S universities, less symmetrical than theoretically proposed, there are indeed signs of stakeholder participation and mutual engagem ent on all of the three sites. Of the three SNSs where data were
92 collected, Twitter generated the greatest probability of dialogic communication between etc. The best example of Twitter dialogic commu nication came from the official Twitter feeds of Arizona State University: eleven out of twenty tweets coded were conversations between the university staff and stakeholders, regarding issues of programme applications, appreciation of stakeholder co ntribut ions, etc Communication symmetry is not only reflected in streams of tweets and wall posts, but also in the design of site navigation tools that could spur dialogic communication Quite a number of SNS dialogic features were identified on university Face book, Twitter, and Weibo sites. These dialogic features allow greater stakeholder institution interactivity, hence relatively more symmetrical communication between institutions and their strategic publics. On Facebook, universities usually list a number of contact information as part of the dialogic loop for stakeholder response; message boards and resource recommendation boards were left for user generated contents. On Twitter, the communication s ymbols were used to generate trends and aggregate popular topics. On Weibo, a combination of Facebook and Twitter dialogic features were identified. Occasionally, stakeholder ich turned the comment boards into an instant messaging system for dialogic communication. Having said that, a mong the samples, there were cases where universities failed to embed a functional message board onto their Facebook and Weibo sites In other c ases, Twitter hash tags for university related topics and trends were shor t of systematic classification and the comment section for institutional response was
93 barely used. The underdevelopment and underuse of SNS dialogic features can partly explain the lack of significant stakeholder response on SNSs, es pecially on Twitter and Weibo. symmetrical than expected. Though provided with a user friendly SNS interface, followers of universi ty SNSs had, at best, some control of navigation, instead of control of communication. On the one hand, u niversities on SNSs, similar to commercial institutions and government agencies, are still in control of the degree of information disclosure, content s of wall posts and tweets, and the way in which contents are presented to their strategic publics O n the other hand SNS followers began to play the collaboratively with the se institutional sites to create communicative trends and generate values, knowingly or not. The D ynamic of SNS C ollaborative N etworking The concept of collaborative networking was first proposed in industrial engineering and business management literature referring to cross sector partnership and a holistic approach to internal and external organizational communication. T he current research tried to find out how collaboration happened and compare the differences of collaborative networking between differ ent SNSs. Two variables were designed for measurement: the diversity of information source and the degree of information aggregation. An important insight emerging from the results is that the ideal situation for is contingent on successful management of a collaboration loop across different social media platforms. The SNS collaboration loop
94 of U.S. universities is composed of two tiers of networks: information ends and social media outlets. The first tier of ne twork is information ends. For universities trying to develop a social map of connections among stakeholders and institutions, information ends may include students, alumni, faculty, affiliated organizations, external news sources, etc., among other strat egic publics. To spur the dynamic of collaboration, an important task for universities is to galvanize these information ends to contribute value to the SNS. Through various initiatives and projects, universities have a chance to turn these information e nds into functional information agents, who could carry messages and trends to an even wider social network The second tier of network is social media outlets. As observed from U.S. duplicated and redefined across different social media outlets. For instance, a great many embedded videos on Facebook and Twitter were from YouTube; embedded videos on Weibo were mostly from Youku, the Chinese video sharing site; quite a few embedded ph otos and pictures on Facebook and Twitter were from Flickr and Instagram. The connection between multiple social media outlets remains a critical link for university SNS stakeholder communication. At the current stage, the connection is achieved by addin g wall posts, and tweets This would help direct site viewers to other social media outlets operated by the universities. A few U.S. universities have developed their own social media dashbo ards where updates on three or four university SNSs are captured i n one single page (See Figure 5 1 ).
95 Statistically, the degree of SNS collaborative networking is positively correlated with the amount of stakeholder response value on Facebook, which means that the higher the value of collaborative networking on a university Facebook site, the more likely stakeholders would share, like, and comment on university wall posts. Though Twitter has the highest CNV among the three SNSs, the amount of stakeholder response value is not statistically correlated with the degree of collaborative networking on the site, and so it is with Sina Weibo. One possible explanation is that neither of the two sites managed to generate significant respo nsive value from stakehold ers. Facebook site features, such as like and share may generate a greater momentum for stakeholder response than Twitter and Weibo. Hence, more researches are needed to explicate the impacts different SNS communication features have on user respons ive behaviors. From the statistical results, we may safely conclude that the collaborative networking dynamic on university SNSs has started growing and more stakeholders need to be invited into the collaboration loop to create responsive and collaborative communication value. Most importantly, universities need to connect and aggregate a structure so as to attract more attentive resources from stakeholders. Cultur al D ifferences on U niversity SNSs The virtual sphere of human communications is essentially cultural driven (Arora, 2012). Social networking sites, as a critical dimension of the Web 2.0 sphere, also have different cultural orientations in terms of conten ts and communication models. In this been carefully analyzed for their cultural characteristics, against four cultural dimensions tional cultures: individualism, collectivism,
96 masculinity, and femininity. Since Sina Weibo is a popular Chinese social networking site, it may or may not contain cultural elements pertaining to the Chinese national culture, which is collectivistic and mo derately masculine (Hofstede, 1991). For U.S universities trying to reach stakeholder groups on Chinese social media, they would have to adapt communication strategies to Chinese cultural traditions. Likewise, Facebook and Twitter may represent a suppose dly more individualistic and masculine U.S. culture (Hofstede, 1991). Cultural differences are expected across the se three SNSs Statistics suggested that there was no significant difference between U.S contents a nd communication strategies in terms of individualism versus collectivism. Overall, information on the three sites indicated a slightly collectivistic orientation, which alluded to the fact that SNSs were mostly used by U.S. universities as official port als for organizational external used as the message subjective in wall posts and tweets. From news about school athletic teams, academic success of individual students, a lumni contributions, to research achievements made by a particular faculty member, the name of the university was often associated or indicated in the context. This is not entirely surprising, given that universities have a strong motive in adopting SNSs for organizational brand management. As for stakeholders who follow a particular university on Facebook or Weibo, the collectivistic elements of SNS contents helped them more easily identify with sity of Illinois at Urbana Champaign, on Jan 19 th 2013, posted on its Facebook wall, the news of the UIUC
97 Alumni Association advocating on behalf of the university during the 2013 inauguration. mong UIUC followers, cementing the bondage between stakeholders and th e institu tion Statistics also showed that there was significant difference between Facebook and Weibo in terms of masculinity versus femininity. Both Facebook and Twitter had a higher mean value of SNS masculinity than Weibo, which means that more contents related to institutional goals and missions, achievements, and competitiveness were being circulated on Facebook and Twitter than on Weibo. On all of the three SNSs, however, there w as more femininity oriented information The overall feminine previous findings that online social networking is driven by social capital development (Ji et al., 2010), real time socialization for connected individuals, or strategic planning and optimization of di gital resources (Sessler, 2009) National cultural differences in terms of masculinity versus femininity were not obvious in the case of U.S universities stak eholder communication on Facebook, Twitter, and Sina Weibo. Implications for T heory and P ractice This research is first of its kind to explore the emerging phenomenon of SNS stakeholder communications and collaborative networking between educational instit way symmetrical communication, the dialogic theory of public relations, and the concept of collaborative networking were integrated and presented as the theoretical underpinning of this re search. Though the research failed to provide statistical evidence for the existence of a two sites, it did reveal a slight paradigm shift from asymmetrical communication to more
98 dialogic and collaborative stakeholder communication on Facebook, Twitter, and Sina Weibo. Grunig (1987) once envisioned the ideal scenario of symmetrical communication to be a holistic, interdependent, and equilibrium communicative process in which organizations and their internal and external stakeholders would reach consents through negations of interests and open dialogues. What underlies both the symmetrical communication model and the dialogic theory of public relations is a change in the power structure of communications from persuasion and manipulation of public opinions to managing communications and negotiating relationships (Ledingham & Bruning, 2000). Though there were signs of institution stakeholder interactivity and dialogues taking pl ace on Facebook, Twitter, and Weibo, the research findings communication platform than suggested in previous literature. Universities, not unlike corporations and government agencies have hardly given up control of their communicative resources on SNSs. Instead of manipulating public opinions in a rather persuasive manner, universities on SNSs are trying to manage stakeholder responses and aggregate stakeholder generated contents in to SNS communication assets cannot be a democratic public space for organizational communication. Rather, universities, among other organizations, can tap into the communicat ion resources and social connections of their stakeholders on SNSs for collaboration and relationship management, given that collaborative networking between universities and stakeholders seems to be a more robust and promising phenomeno n on SNSs than open dialogues.
99 This study, therefore, proposes another paradigm shift, especially for SNS mediated stakeholder communication and public relations: from persuasion and dialogues to collaborative networking. SNS collaborative networking is essentially an integ rated model of organizational strategic planning, open source development, and mutual engagement with stakeholders. The overarching objective of SNS collaborative networking is strategic partnership formation and joint value creation between organizations and stakeholders. SNS collaborative networking is essentially an evolving and flexible concept, open to creative interpretation and application. It can be achieved through dialogic communication, crowdsourcing, or open source sharing, with or without in stitutions in charge of the communicative process. With digital technologies and online social networking services, what organizations are capable of achieving is not only collaborative planning and issue management with stakeholders (Kearns and West, 199 6), but also creating a collaboration loop in which stakeholders can play a role of content generation, information dissemination, and strategic decision making. There may be several ways that collaborative networking on SNSs can be brought into full play and it behooves of public relations professionals to identify the potential trends of collaboration and develop strategic plans to apply this integrated model of collaborative networking to an increasingly intelligent web of businesses, technologies, and communications. Another important implication from this research is that SNSs need to be operated as a multidimensional cultural sphere. In some senses, SNSs are born to be a transnational phenomenon. Users from all national, ethnic, and cultural backgro unds can join communities and manage social relations on SNSs. However, for universities
100 trying to expand brand influence and manage stakeholder relations in foreign markets, it is critical that cultural differences are taken into consideration when devel oping SNS communication strategies. To build and successfully maintain a global network of stakeholder relations systematic and specific mechanism to understand the expectations, motives, and co mmunicative needs of their stakeholders from different cultural backgrounds. The expectation is that stakeholder communication would be much more effective if the organizational SNS contents were carefully designed to observe the cultural traditions of a foreign public. Limitations and S uggestions for F uture R esearch: stakeholder communication. Firstly, convenient samples were adopted from multiple external lists. As a result, o n ly U.S universities with a large international student population were included in the study sample. Most of the sampled universities are well established and accredited educational institutions that already have a fair share in the market of internationa l education. Community colleges, private education services, or universities and colleges that have less international recognition were not included in the sample. Therefore, research results regarding the trends and characteristics of SNS stakeholder co mmunication may not be generalized to the entire population of education service providers in the United States. Secondly, communication trends on SNSs are changing and evolving rapidly, therefore quantitative content analysis can only capture one fleetin g moment of SNS communication. There are possibilities that universities may exhibit different communication patters and coll aborative tendencies outside the period of research observation therefore, the content analysis results reflect
101 only a fragment o f this complex phenomenon of SNS media ted stakeholder communication. Further researches are needed to test the concepts, findings, and conclusions of the current study and add more qualitative and in depth dimensions to the academic understanding of SNS st akeholder communication and collaborative networking. To begin with, future studies may explore other possible dimensions of SNS collaborative networking, apart from diversity of information source and degree of information aggregation. In depth intervie university leaders, and various stakeholder groups may shed insight on how SNS collaboration can be played out in different communication scenarios: for instance, crisis communication, emergency informa management, etc. In this research, significant differences were found between Facebook, Twitter, and Weibo, in areas of cultural orientations, communication symmetry, and the degree of collaborative netw orking. In the future, researchers may compare SNS differences, in terms of SNS structures, design features, site functionalities, etc. Additionally, researchers may further explore the nature of SNS communicative features, such as Facebook like and Tw itter retweet and explain whether these features are correlated with specific user responses. A more specific diversification of SNSs according to site communication features may help public relations scholars and professionals deploy communicative res ources more wisely and run campaigns more effectively on the SNS of choice L ast but not least, researchers may adopt a micro thematic approach to analyze SNS contents. In the research context of university public relations and strategic communications, researchers may
102 look into the relationships between SNS fashions, trends, topics, and the dynamic of stakeholder response, or simply ask the question: what kinds of SNS topics will generate most attention, behavioral response, and content creation from sta keholders. To recap: this research explores the concept of symmetrical communication and d ynamism, an d compare the differences of cultural orientations on multiple SNSs As the evolution of web based communications enters the age by John Markoff of the New York Times, communication scholars have an urgent mandate to advance theories and models to reflect the changes. This early, exploratory study on SNS mediated public relations and strategic communications is only a small step to that end. Figure 5 1 An example of university social media dashboard. Northeastern University http://www.northeastern.edu/social media/
103 APPENDIX A C ODEBOOK: SNS CONTENTS This codebook includes instructions for the coding process and lists of items for each variable, which will help coders decide on the completeness of university SNS profile; identify the communication strategy of wall posts and tweets and the presence or absence of collaborative networking and cultural differences along designated dimensions; and ultimately ans wer questions about operationalization. Instructions: ID and Independent Variables 1. ID Number: U niversity name on Facebook, Twitter handle, and Weibo handle will be recorded, as the identification number for the unit of analysis. 2. Independent variable s: I nstitution type: public, or private History of university SNS: calculated by the number of months during which an official account is active Completeness of SNS Profile Researchers will code the presence or absence of the following items, the degree of completeness is decided by the number of items each profile contains. 1. Facebook A total of ten categories are identified for Facebook profile : Map/Location and address Contact information Contact information include email addresses and telephone numbers Links to external web sources External web sources may include university official website, blogs, website for u ni versity admission office Links to other social media applications Other social media applications may include: Twitter, YouT ube, Flickr, iTunes instragram, and pinterest 2. Twitter A total of six categories are identified for Twitter profile :
104 Year of found ation University location Links to official university websites School logo Motto or slogan Description about the university Involvement: words that encourage student participation 3. Weibo A total of seven categories are identified for Facebook profile : C telephone numbers Description about the university Promotion slides Introduction video Links to official university websites Admission information Identity tags (exact contents will be recorded): university may have several identity tags which serve the function of key words in the Weibo search engine Stakeholder Communication Strategies Firstly, each wall post or tweet will be coded into the three communication strategy categor Depending on the degree of communication symmetry, each stakeholder communication strategy will be assigned a numerical value: information dissemination Information Dissemination The communicative purpose of this type of message is to subsidize stakeholders with facts, statistics, past event information, etc, in relation to the particular university 1. Facebook the following items: News with hyperlinks Photos Videos Status updates: status updates are posted by the university and usually do not contain links to external news sources. 2. Twitter following items: News with hyperlinks Photos
105 Videos Public messages: public messages can be original tweets or retweets and are used by universit ies as announcements or statements on Twitter. 3. Weibo following items: News with hyperlinks Photos Videos Public messages: public messages can be original tweets or retwee ts and are used by universities as announcements or statements on Weibo. Involvement encourage users to go to other web sources of the university and usually contains links participate a certain event organized by the university or its affiliated organization s. The communicative purpose of this type of message is to involve stakeholders into certain events or activities, in relation to the particular university. Researchers will code the presence or absence of the two items. 1. Facebook Conservation of visits Georgetown is about to begin. Join the live chat here: http://ow.ly/gGgXn Invitation to events comment with your best caption! #Northeastern # Caption 2. Twitter Conservation of visits @uscthornton : Check out Thornton's spring semester events calendar: http://fb.me/1ODqVtdVb Invitation to events 2pm, for the Spring Involvement Fair 350 student orgs & depts. http://ow.ly/gS89q 3. Weibo Conservation of visits Invitation to events Dialogue Mutuality and propinquity are two overarching dialogic tenets (Kent & Taylor,
106 communicative purpose of this type of message is to initiate conversations between the university and its stakeholders, or among stakeholders themselves. 1. Facebook : Wall posts that are designed to initiate online conversations or offline responses Wall posts that appear on the university timeline, posted by fans or others Tags that appear on the university timeline, posted by fans or others 2. Twitter : Tweets from stakeholders with communication values added Retweets as replies to stakeholder requests o r questions University tweets that initiate online conversations or offline responses 3. Weibo : Tweets from stakeholders with communication values added Retweets as replies to stakeholder reque sts or questions University tweets that initiate online conversations or offline responses The Dialogic F eatures of SNS SNSs can be an ideal communication platform for symmetrical communication. Researchers will identify the number of dialogic features of Twitter, and Weibo sites, as a reflection of communication symmetry on SNSs. Aligned with the value structure for communication strategy, the presence of one dialogic wall post or tweet would generate. The aggregate amount of symmetrical SNS value for the entire si te will be calculated. Dialogic features of SNSs may include, but are not limited to the following items: Contact information for th e institution (telephone number, email address, etc) An active message board, where users can post ques tions or replies to the message A place for stakeholder recommendation of external sources, such as the The use of c ommunication symbols to assemble sta ideas such as a unique hash tag for university related topics Embedded applications that all ow better information harvest Dialogue in the comment section: university may employ the comment board to c ommunication with stakeholders The use of wall posts, tags, or retweets to answer stake holder questions (will be coded separately in the strategy type section)
107 SNS Communication Symmetry The communication symmetry value of a SNS is calculated by addin g up the numeric values of stakeholder communication strategy for each wall post or tweet coded and the value of SNS dialogic feature. 1. Facebook Sum of stakeholder communication strategy value for each wall post Sum of dialogic feature value for each sit e 2. Twitter Sum of stakeholder communication strategy value for each tweet Sum of dialogic feature value for each site 3. Weibo Sum of stakeholder communication strategy value for each tweet Sum of dialogic feature value for each site Collaborative Networ king Firstly, numerical scales will be used to measure the diversity of SNS information source. Secondly, the degree of information aggregation will be determined by the number of communication tools used for the entire site. 1. Diversity of Information Source Researchers will determine where the information (posts or tweets) comes from originally. Twelve categories for inf ormation sources are identified : Administrator University news sites Other social media platforms for the university Affiliations Fa culty & Staff Current students Prospective students Alumni External news sources Celebrities on Twitter Organizational websites Others 2. Information Aggregation several SNS communi cation tools in a single wall post or tweet. Information is aggregated when the university SNS shares news contents from external sources, creates conversations, topics, and discussion trends among the SNS community using tags, hash tags, or other communi cation tools.
108 Facebook: Embedded hyperlinks In text hyperlinks to other Facebook sites Embedded pictures or photos Embedded videos Embedded applications Tags (University Facebook site tagging other information sources or being tagged) Twitter: Embedded hyp erlinks @replies Retweets from other information sources Modified tweets (MT) Hash tags Embedded news summary Embedded photos Embedded videos Embedded applications Weibo : Embedded hyperlinks Retweets from other information sources Hash tags Embedded photos or pictures Embedded videos Embedded applications The Response Mechanism of SNS Users The response mechanism of SNS users consists of two parts: numerical and may also leave a comment under a wall post or tweet. The attributes of comments are tive attitudes towards the news, issues, and events described in a wall post or tweet, or is an expression of affectionate emotions towards the particular university. A nega tive suspicion, or disbelief towards the news, issues, and events described in a wall post or iversity policies, or a particular university faculty or staff. A neutral or mixed comment does not indicate favorable or unfavorable stakeholder attitudes, but contains factual statements, objective evaluations, or communication symbols, bereft of emotio nal values. If a comment does not address the content of a wall post or tweet, it will be coded as irrelevant. Positive is coded as 1 in value, negative as 1, neutral/mixed as 0. The attribute value of comments for a particular post or tweet and that fo r the entire site will
109 numerical measure for the entire site will be calculated and record ed. 1. Facebook Researchers will code the attribute of comments as positive, neutral/mix ed, negative, or no relevance 2. Twitter Researchers will count the number of secondary re tweets (retweet s by followers) and Comments and conversations will be coded as positive, neutral/m ixed, negative, or no relevance 3. Weibo Comments will be coded as positive neutral/mixed, negative, or no relevance Cultural Dimensions 1. Individualism vs. Collectivism (IDV): Researchers will code whether the content is more concerned with individuals, or groups/organizations. Individualistic contents are coded as 2 in value collectivistic as : M easured by the presence or absence of a wall post or tweet that highlights one or several par ticular individuals as subjects : M easured by the presence or absence of a wall post or tweet that highlights grou ps or organizations as subjects i f the message is too short or vague to reflect any specific 2. Masculinity vs. Femininity (M AS) Researchers will code whether the contents of a wall post or tweet is about achievements of the university, affiliated researchers, university staff, alumni, current (masculinity); or relationship development and student life at the university (femininity). Masculinity :
110 M easured by the presence or absence of a wall post or tweet that highlights the Femininity : M easured by the presence or absence of a wall post or tweet that highlights the quality of student life on campus or rela tionship development efforts by the unive rsity r vague to reflect any specific cultural dimensions, it will be c
111 APPENDIX B CODE SHEET 1: FACEBOOK, TWITTER, AND WEIBO SITE ID and Independent Variables 1. ID Na me/Handle 2. Institution type: Public Private 3. History of SNS use Completeness of Profile 1. Facebook Map/Location and address Contact information Link to external web sources Links to other social media applications 2. Twitter Year of foundation University location Links to official university websites School logo Motto or slogan Description Involvement 3. Weibo Cont act information Description Promotion slides Introduction video Links to official university websites Admission information Identity tags Communication Strategies Information Dissemination :
112 1. Facebook News with hyperlinks Photos Videos Status u pdates 2. Twitter News with hyperlinks Photos Videos Public message 3. Weibo News with hyperlinks Photos Videos Public messages Involvement : 1. Facebook Conservation of visits Invitation to events 2. Twitter Conservation of visits Invitation t o events 3. Weibo Conservation of visits Invitation to events Dialogue : 1. Facebook Wall posts to initiate online conversations or offline responses Wall posts posted by fans or others Tags posted by fans or others 2. Twitter Tweets from stakeholders with communicat ion values added Retweets as replies to stakeholder requests or questions University tweets that initiate online conversations or offline responses 3. Weibo Tweets from stakeholders with communication values added Retweets as replies to stakeholder requests or questions
113 University tweets that initiate online conversations or offline responses The Dialogic F eatures of SNS Facebook/Twitter/Weibo: Contact information for the institution An active message board for stakeholder requests a nd questions A communication board for external resources Site navigation tools Communication symbols to assemble information and create trends Embedded applications that allow better information harvest s section) SNS Communication Symmetry 1. Facebook Sum of stakeholder communication strategy value for each wall post Sum of dialogic feature value for each site 2. T witter Sum of stakeholder communication strategy value for each Twitter tweet Sum of dialogic feature value for each site 3. Weibo Sum of stakeholder communication strategy value for each Weibo tweet Sum of dialo gic feature value for each site Collabor ative Networking Diversity of Information Agents : Facebook/Twitter/Weibo: Administrator University news sites Other social media platforms for the university Affiliations Faculty & Staff Current students Prospective students Alumni External news s ources Celebrities on Twitter Organizational websites Others
114 Information Aggregation : 1. Facebook Embedded hyperlinks In text hyperlinks to other Facebook sites Embedded pictures or photos Embedded videos Embedded applications Tags 2. Twitter Emb edded hyperlinks @replies Retweets from other information sources Modified tweets (MT) Hash tags Embedded news summary Embedded photos Embedded videos Embedded applications 3. Weibo Embedded hyperlinks Retweets from other information sources Has h tags Embedded photos or pictures Embedded videos Embedded applications The Response Mechanism of SNS Users 1. Facebook Attributes of comments Positive Negative Neutral/mixed No rele vance 2. Twitter is calculated Attributes of comments and conversations Positive Negative Neutral/mixed
115 No relevance 3. Weibo is calculated Attributes of comments and conversations Positive Negative Neutral/mixed No relevance Cultural Dimensions 1. Individualism vs. Collectivism (IDV): Facebook/Twitter/Weibo: Individualistic Collectivis tic 2. Masculinity vs. Femininity (MAS) : Facebook/Twitter/Weibo: Masculine Feminine
116 APPENDIX C CODE SHEET 2: FACEBOOK WALL POSTS; TWITTER TWEETS; AND WEIBO CONTENTS ID Number for wall posts and tweets Facebook Communication strategy type Informati on Dissemination: 1 Involvement: 2 Dialogue: 3 Comment value for wall posts: Positive: 3 Neutral: 2 Negative: 1 No relevance: 0 IDV Individua lism: 1 Collectivism: 2 Cannot be categorized: 0 MAS Masculinity: 1 Femininity: 2 Cannot be categorized: 0 Twitter Communication strategy type Information Dissemination: 1 Involvement: 2 Dialogue: 3 The number of retweet s for a particular tweet Comment value for tweets: Positive: 3 Neutral: 2 Negative: 1 No relevance: 0 IDV Individualism: 1 Collectivism: 2 Cannot be categorized: 0 MAS Masculinity: 1
117 Femininity: 2 Cannot be categorized: 0 Weibo Communication strategy type Information Dissemination: 1 Involvement: 2 Dialogue: 3 The number of retweets for a particular tweet Comment valu e for tweets: Positive: 3 Neutral: 2 Negative: 1 No relevance: 0 IDV Individualism: 1 Collectivism: 2 Cannot be categorized: 0 MAS Masculinity: 1 Femininity: 2 Cannot be categorized: 0
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130 BIOGRAPHICAL SKETCH Y anqun Lou receiv ed her M AMC degree from the University of Florida in the summer of 2013. B efore she came to the United States, Yanqun had received her bachelor deg ree in English literature from Shanghai University, where she was recognized for outstanding academic performan ce and public speaking talents. While pursuing her master s degree at the University of Florida Yanqun worked hard on her studies of intercultur al communication, international public relations, and social media communication. She was recognized for her international perspectives, intelligence, and dedication to global communication. supervised by Prof. Juan Carlos Mol leda.