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Session 4C [clear filter]
Sunday, September 28
 

10:20

Session 4C: Opinions and Influencers
"#ReputableNewsSource? How Twitter and an Online Community of Sources Contributed to the Legitimation of Andrew Breitbart."
Gillian Brooks

"Social Media Rumors as Improvised Public Opinions: A Semantic Network Analysis of Twitter during Korean Saber Rattling 2013."•
K. Hazel Kwon and C. Chris Bang

"Topic Modeling with Sentiment Evaluation for Analysis of Opinion Polarization."
Gabe Ignatow, Nick Evangelopoulos and Konstantinos Zougris

"Traces of Influence: Understanding Opinion Leaders in Context."
Elizabeth Dubois

Moderators
JB

Jacquie Burkell

Associate Vice President, Research, Western University
Social impact of technology, privacy, technology in the justice sector

Speakers
CC

C. Chris Bang

University at Buffalo - SUNY
GB

Gillian Brooks

Centre for Corporate Reputation, Said Business School, University of Oxford
avatar for Elizabeth Dubois

Elizabeth Dubois

DPhil (PhD) candidate, Oxford Internet Institute
University of Oxford, United Kingdom
NE

Nick Evangelopoulos

University of North Texas
GI

Gabe Ignatow

Associate Professor, University of North Texas
text mining, text analysis methods, sociology, theory, Bourdieu, new media And I love to talk about my startup company GradTrek.com, a graduate school recommendation engine (similar to Match.com and Pandora).
avatar for K. Hazel Kwon

K. Hazel Kwon

Assistant Professor, Arizona State University
KZ

Konstantinos Zougris

University of North Texas


Sunday September 28, 2014 10:20 - 11:40
TRS 1-149 Ted Rogers School of Management

10:21

"#ReputableNewsSource? How Twitter and an Online Community of Sources Contributed to the Legitimation of Andrew Breitbart"

Background: Traditional news organizations exist within an apparatus of accountability, held together by their reputation and the professionalization of the occupation of journalism. Legitimacy in journalism has been solidified over time, but with the emergence of online media, traditional journalistic standards have been challenged as online news organizations attempt to create a new standard to define the different kinds of journalistic practices that are occurring online and the role played by social media in this process. According to Pierre Bourdieu (1998), the standards that define whether a news organization is legitimate are based on whether those occupying dominant positions in the field recognize it as such. Recognition by someone who is considered legitimate grants legitimacy.

Objective: This paper explores the changing nature of the profession of journalism as a space of contested power relations and networked communities, focusing specifically on how a controversial online news organization – Breitbart.com – became a legitimate source for news. Using both the Anthony Weiner and the Association of Community Organizations for Reform Now (ACORN) scandals, this paper highlights Breitbart’s reliance on his online community, a distinct group of followers which I have termed “outlier sources” - individuals who have experienced or been part of a news event and can provide a first-hand account of what took place. With the mainstream media fearing Breitbart, it was clear that he was never going to receive press releases and tips from the establishment. As a result, he needed access to sources that could provide him with “the goods”. He positioned himself in the field as an outspoken critic of the left, encouraging like-minded individuals to reach out to him as sources, gaining legitimacy initially amongst the extreme right, later from mainstream media.

Methods: Ethnographic research was used to gain a greater understanding of Andrew Breitbart and his five websites. I conducted over 60 hours of interviews in Los Angeles with Breitbart in November 2011, five months before his death. I embedded myself in his environment, shadowing him daily from 9:00 a.m. to 10:00 p.m., at his office, his home, at meetings and at appointments. I transcribed and coded the interviews, highlighting informal references to Bourdieu’s principle of legitimation: peer and/or public recognition (1998). I also interviewed his co-workers at Breitbart.com. In addition to my ethnography, I examined the tweets that were posted during the initial Anthony Weiner allegations. I also analyzed the transcripts that were recorded during the undercover investigations at three ACORN locations in the United States.

Results:  In examining legitimacy and how it is achieved in the field of journalism, I established that the use of social capital was at the center. The field is strengthened not only by economic profit, but also through networking (a form of social capital). Specifically, Breitbart emerged as a legitimate player by creating a position for himself where those with similar views could approach him online with news tips and scoops. My study revealed that Breitbart’s websites comprise a conservative echo chamber where he has emerged as a mouthpiece for the Tea Party, subsequently encouraging like-minded readers to contact him with story ideas, enabling him to use them as sources.

Conclusions: An organization’s ability to gain legitimacy in the field of journalism is dependent on its capacity to leverage varying levels of social capital online. Understanding the use of social capital illustrates the increasingly networked nature of this evolving field, whereby the maintenance of online relationships is paramount.  

References: 
Bourdieu, Pierre. (1998). On Television and Journalism. London: Pluto Press


Speakers
GB

Gillian Brooks

Centre for Corporate Reputation, Said Business School, University of Oxford


Sunday September 28, 2014 10:21 - 10:40
TRS 1-149 Ted Rogers School of Management

10:41

"Social Media Rumors as Improvised Public Opinions: A Semantic Network Analysis of Twitter during Korean Saber Rattling 2013"

Background:  Understanding public opinion is one of the most challenging tasks for communication/political scholars (Herbst, 1991). In contrary to an institutionalized and top-down construction of public opinion climate, most notably via “polling” systems, recent social media sites manifest citizens’ improvised opinion sharing, thus provide alternative indicators of spontaneous, bottom-up opinion climates. In particular, “rumors” that spread in social media represent “affect-laden” collective reactions to uncertainties (Peterson & Gist, 1951) and reveal publics’ hopes, fears, anxieties and/or hostilities (Oh, Kwon, & Rao, 2010; Oh, Manish, & Rao, 2013). Social media archives help to revive textual studies of rumors by allowing an easy access to otherwise ephemeral and time-sensitive rumor stories. Among different types of rumors, hostile rumors (Knapp, 1944; Allport & Postman, 1947; Garrett, 2011) reflect negative subcultural opinion climates, of which understanding may contribute to identify structures of social relations embedded in a society and subconscious sources of intergroup hostility.

Objective: This paper aims to explore semantic structures of hostile rumors spread in social media. By leveraging Twitter messages shared during an event of South-North Korea saber rattling in 2013, the paper highlights topical clusters of hostile rumors in comparison with non-rumor messages. The goal is to conduct a preliminary analysis to show how online rumormongering mirrors socio-historical antecedents of political schism, and how such antecedents are intertwined with a collective process of uncertainty reductions under a social crisis. 

Methods: The study analyzes 2,500 unique tweets that were quota-sampled based on retweet frequencies. First, manual content analyses were conducted to distinguish hostile rumors from non-rumors. A series of z-tests was then conducted to identify which words/concepts occurred more prominently in one group than the other. Semantic network analyses (Yuan, Feng, & Danowski, 2013; Doerfel & Barnett, 1999) were conducted based on the co-occurrence matrices among these identified words/concepts. To address semantic structures in each text network, the Clauset-Newman-Moore clustering algorithm was employed.

Results: Semantic network analyses revealed four topical clusters from rumor messages, and three clusters from non-rumor messages. In the non-rumor network, the major themes were (a) government’s military strategies to the threat (Cluster 1), (b) international organizational response (Cluster 2), and (c) North Korea’s international relations (Cluster 3). In the rumor network, the emerged themes were (a) connections between particular politicians/events and North Korea (Cluster 1), (b) social and religious entities’ responses to the threat (Cluster 2), (c) Cold-war metaphors (Cluster 3), and (d) satires about Congress (Cluster 4). The comparisons between semantic structures reveal that non-rumor messages mainly discusses about institutional, formal measures to reduce uncertainty. On the other hand, hostile rumors uncover a hidden side of public mind, including skepticism about government’s readiness and intergroup polarity deeply rooted in ideology of the Cold war era (See Figures).

Conclusions: Social media data gives an unprecedented opportunity for political/communication scholars to explore improvised public opinion climates, especially under a crisis. In this preliminary study, we conducted semantic network analyses of Twitter messages during Korean threat situation 2013 to explore topical differences between rumors and non-rumor messages. Textual studies of online rumors can help in understanding informal process of collective interpretation of the situation and revealing subconscious public mind in a socio-historical context. While this study relied on manual content analysis to identify rumors, machine-learning detection of rumors will help scale up the scope of analysis.

References: 
Allport, G. W. & Postman, L. (1947). An analysis of rumor. The Public Opinion Quarterly, 10(4), 501-517

Doerfel, M. L., & Barnett, G. A. (1999). A semantic network analysis of the International Communication Association. Human Communication Research, 25(4), 589-603.

Garrett, R. K. (2011). Troubling consequences of online political rumoring. Human Communication Research, 37, 255-274.

Herbst, S. (1991). Classical democracy, polls, and public opinion: Theoretical frameworks for studying the development of public sentiment. Communication Theory, 1(3), 225-238.

Knapp, R. (1944). A psychology of rumor, The Public Opinion Quarterly 8, 22–37.

Oh, O., Kwon, K. H., & Rao, H. R. (2010). An exploration of social media in extreme events: Rumor theory and twitter during the Haiti earthquake 2010.

Oh, O., Agrawal, M., & Rao, H. R. (2013). Community intelligence and social media services: A Rumor theoretic analysis of Tweets during social crises. Management Information Systems Quarterly, 37(2), 407-426.

Peterson, W. A., & Gist, N. P. (1951). Rumor and public opinion. American Journal of Sociology, 159-167.

Yuan, E. J., Feng, M., & Danowski, J. A. (2013). “Privacy” in Semantic Networks on Chinese Social Media: The Case of Sina Weibo. Journal of Communication, 63(6), 1011-1031.

 


Speakers
CC

C. Chris Bang

University at Buffalo - SUNY
avatar for K. Hazel Kwon

K. Hazel Kwon

Assistant Professor, Arizona State University


Sunday September 28, 2014 10:41 - 11:01
TRS 1-149 Ted Rogers School of Management

11:01

"Topic Modeling with Sentiment Evaluation for Analysis of Opinion Polarization"

Background: It is widely recognized that U.S. national politics have become more polarized over the last several decades, and that the proliferation of partisan news outlets (talk radio stations, partisan news channels, news web sites, and blogs) has contributed to public opinion polarization. While qualitative research has identified a number of rhetorical strategies used by partisan news outlets, including overgeneralization, sensationalism, misleading and inaccurate information, ad hominem attacks, and belittling ridicule of opponents, that produce polarizing emotional reactions in audiences (Sobieraj and Berry 2011), research on how consumption of partisan news may influence audience attitudes has been held back by measurement problems (Prior 2013).

Objective: We present a new text analysis technique, topic modeling with sentiment evaluation (TMSE), that combines four methodological elements (precise multiple-sample selection, topic models with latent semantic analysis, sentiment analysis, and correspondence analysis) in order to compare the degree of polarization of topics across text collections produced by social groups.

Methods: We demonstrate TMSE by analyzing reactions to the Trayvon Martin controversy in spring 2012 by commenters on two partisan news websites (the Daily Caller and the Huffington Post, with approx. 4000 lines and 130,000 words per sample).

Results: Based on studies of news media as an outrage industry (Berry and Sobieraj 2014) and of political pundit inaccuracy (Tetlock 2006), we predict that high-profile commentators will be more polarizing than other news personalities and topics. Results of the TMSE analysis support this prediction.

References: 
Berry, J. M., and S. Sobieraj. (2014). The outrage industry: Political opinion media and the new incivility. Oxford, UK: Oxford University Press.

Prior, M. (2013). Media and political polarization. Annual Review of Political Science, 16, 101-127.

Sobieraj, S., J. M. Berry. (2011). From incivility to outrage: Political discourse in blogs, talk radio, and cable news. Political Communication, 28(1): 19-41.

Tetlock, Philip E. (2006). Expert political judgment: How good is it? How can we know? Princeton, NJ: Princeton University Press.


Speakers
NE

Nick Evangelopoulos

University of North Texas
GI

Gabe Ignatow

Associate Professor, University of North Texas
text mining, text analysis methods, sociology, theory, Bourdieu, new media And I love to talk about my startup company GradTrek.com, a graduate school recommendation engine (similar to Match.com and Pandora).
KZ

Konstantinos Zougris

University of North Texas


Sunday September 28, 2014 11:01 - 11:20
TRS 1-149 Ted Rogers School of Management

11:21

"Traces of Influence: Understanding Opinion Leaders in Context"

Background: “Opinion leaders” are influential members of society who are thought to use social pressure and social support to transmit media messages to the wider public (Katz & Lazarsfeld 1955). While opinion leaders once relied on the mass media to receive messages and face-to-face and telephone communication to transmit messages, in a new hybrid media system (Chadwick 2013) new tools and options exist.

Objective: The aims of this paper are twofold. First, the paper highlights the utility of incorporating digital data and visualizations of personal networks in the interview setting. Second, the paper aims to describe the ways in which opinion leaders make use of varying media tools in the process of transmitting political messages.

Methods: Twenty Canadian opinion leaders, all active on Twitter and interested in politics, are treated as mini case studies. Data collection of personal Twitter and Facebook networks, as well as other news media and social media used by that individual is conducted for a two week period. Following data collection, an in-person interview is conducted with each participant. During this interview the offline social network of each individual is elicited and visualizations of online networks are discussed and interpreted jointly by the researcher and participant.

Results: This mixed methods approach revealed that opinion leaders in this sample rely on a variety of tactics and tools to deliver political messages depending on factors such as identity performance per setting, topics, and events. In other words, opinion leadership in these cases is highly contextual.

Conclusions: Incorporating digital data and visualizations into the interview setting allows for the contextualization of findings. The specificity and quantifiable nature of digital trace data paired with insight from thoughtful reflection by the actor during the interview help tease out the intricacies of political messaging and opinion leadership. The chance to comment on, and help interpret data, also provides participants the opportunity to strengthen the dataset by filling in gaps and correcting misinformation while also providing explanations for why certain actions took place.

References: 
Chadwick, A. (2013). The Hybrid Media System. New York: Oxford University Press.

Katz, E. and Lazarsfeld, P. (1955). Personal Influence. Glencoe, Ill : Free Press.


Speakers
avatar for Elizabeth Dubois

Elizabeth Dubois

DPhil (PhD) candidate, Oxford Internet Institute
University of Oxford, United Kingdom


Sunday September 28, 2014 11:21 - 11:40
TRS 1-149 Ted Rogers School of Management