Valence-based homophily on Twitter: Network Analysis of Emotions and Political Talk in the 2012 Presidential Election

This study integrates network and content analyses to examine valence-based homophily on Twitter or the tendency for individuals to interact with those expressing similar valence. During the 2012 federal election cycle, we collected Twitter conversations about 10 controversial political topics and mapped their network ties. Using network analysis, we discovered clusters—subgroups of highly self-connected users—and coded messages in each cluster for their expressed positive-to-negative emotional valence, level of support or opposition, and political leaning. We found that valence-based homophily successfully explained the selection of user interactions on Twitter, in terms of expressed emotional valence in their tweets or support versus criticism to an issue. It also finds conservative voices to be associated with negatively valenced clusters and vice versa. This study expands the theory of homophily beyond its traditional conceptualization and provides a new understanding of political-issue interactions in a social media context.

[1]  Erik Brynjolfsson,et al.  Electronic Communities: Global Villages or Cyberbalkanization? (Best Theme Paper) , 1996, ICIS.

[2]  F. Heider.  The psychology of interpersonal relations , 1958 .

[3]  Davide Buscaldi,et al.  From humor recognition to irony detection: The figurative language of social media , 2012, Data Knowl. Eng..

[4]  Susan T. Fiske,et al.  Category-based versus piecemeal-based affective responses: Developments in schema-triggered affect. , 1986 .

[5]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[6]  S. Chaiken,et al.  The generality of the automatic attitude activation effect. , 1992, Journal of personality and social psychology.

[7]  Lada A. Adamic,et al.  The political blogosphere and the 2004 U.S. election: divided they blog , 2005, LinkKDD '05.

[8]  J. M. Kittross.  The measurement of meaning , 1959 .

[9]  Spencer F. Tinkham,et al.  A diagnostic approach to assessing the impact of negative political television commercials , 2009 .

[10]  Barry Wellman,et al.  Are personal communities local? A Dumptarian reconsideration☆ , 1996 .

[11]  Larry Percy.  The Role of Emotion in Processing Advertising , 2012 .

[12]  Russell H. Fazio,et al.  Attitudes as object-evaluation associations: Determinants, consequences, and correlates of attitude accessibility. , 1995 .

[13]  L. Verbrugge.  The Structure of Adult Friendship Choices , 1977 .

[14]  Jan Kleinnijenhuis,et al.  A test of rivaling approaches to explain news effects: News on isue positions of parties, real-world developments, support and criticism, and success and failure , 2007 .

[15]  R. Garrett.  Politically Motivated Reinforcement Seeking: Reframing the Selective Exposure Debate , 2009 .

[16]  Jan Skopek,et al.  Who Contacts Whom? Educational Homophily in Online Mate Selection , 2011 .

[17]  Arun Sundararajan,et al.  Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks , 2009, Proceedings of the National Academy of Sciences.

[18]  M. Thelwall.  Homophily in MySpace , 2009, J. Assoc. Inf. Sci. Technol..

[19]  James Price Dillard,et al.  Affect and Persuasion , 2000, Commun. Res..

[20]  Xianggui Qu,et al.  Multivariate Data Analysis , 2007, Technometrics.

[21]  Gabriel S. Lenz,et al.  Reassessing the Role of Anxiety in Vote Choice , 2008 .

[22]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[23]  Luciano Rossoni,et al.  Models and methods in social network analysis , 2006 .

[24]  Linda Shields,et al.  Content Analysis , 2015 .

[25]  R. Huckfeldt,et al.  The Social Calculus of Voting: Interpersonal, Media, and Organizational Influences on Presidential Choices , 2002, American Political Science Review.

[26]  H. Brosius,et al.  Instrumental Actualization: A Theory of Mediated Conflicts , 1991 .

[27]  Colin Seymour-Ure,et al.  Content Analysis in Communication Research. , 1972 .

[28]  Bei Yu,et al.  Exploring the characteristics of opinion expressions for political opinion classification , 2008, DG.O.

[29]  Jon D. Morris.  Theories of Emotion and Affect in Marketing Communications , 2012 .

[30]  Esther Thorson,et al.  Perceived Persuasive Effects of Product Commercials and Public Service Announcements , 1992 .

[31]  Ben Shneiderman,et al.  Tweeting Apart: Applying Network Analysis to Detect Selective Exposure Clusters in Twitter , 2013 .

[32]  M. Lorr,et al.  A semantic differential mood scale. , 1988, Journal of Clinical Psychology.

[33]  Gilad Ravid,et al.  An empirical exploration of mass interaction system dynamics: individual information overload and Usenet discourse , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[34]  Young Min Baek,et al.  Online versus face-to-face deliberation: Who? Why? What? With what effects? , 2012, New Media Soc..

[35]  K. Mcgraw,et al.  Memory for political actors: Contrasting the use of semantic and evaluative organizational strategies , 1991 .

[36]  R. Huckfeldt,et al.  Citizens, Politics and Social Communication: Information and Influence in an Election Campaign , 1995 .

[37]  H. Richardson.  Community of Values as a Factor in Friendships of College and Adult Women , 1940 .

[38]  P. Kenney,et al.  Presidential Prenomination Preferences and Candidate Evaluations , 1988, American Political Science Review.

[39]  Jennifer Neville,et al.  Randomization tests for distinguishing social influence and homophily effects , 2010, WWW '10.

[40]  Ben Shneiderman,et al.  Analyzing Social Media Networks with NodeXL: Insights from a Connected World , 2010 .

[41]  J. Russell.  Pancultural Aspects of the Human Conceptual Organization of Emotions , 1983 .

[42]  M. Holbrook,et al.  Assessing the Role of Emotions as Mediators of Consumer Responses to Advertising , 1987 .

[43]  R. Larsen,et al.  Intensity and frequency: dimensions underlying positive and negative affect. , 1985, Journal of personality and social psychology.

[44]  John H. Aldrich,et al.  A Social Cognitive Model of Candidate Appraisal , 1990 .

[45]  Marshall W. Van Alstyne,et al.  Electronic Communities : Global Village or Cyberbalkans ? , 1996 .

[46]  F. Heider.  Attitudes and cognitive organization. , 1946, The Journal of psychology.

[47]  Patrick J. Kenney,et al.  The Slant of the News: How Editorial Endorsements Influence Campaign Coverage and Citizens' Views of Candidates , 2002, American Political Science Review.

[48]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[49]  Isabell M. Welpe,et al.  Election Forecasts with Twitter - How 140 Characters Reflect the Political Landscape , 2011 .

[50]  L. Festinger,et al.  A Theory of Cognitive Dissonance , 2017 .

[51]  Mike Thelwall,et al.  Sentiment strength detection for the social web , 2012, J. Assoc. Inf. Sci. Technol..

[52]  M. Kalmijn,et al.  Intermarriage and homogamy: causes, patterns, trends. , 1998, Annual review of sociology.

[53]  Mike Thelwall.  Emotion Homophily in Social Network Site Messages , 2010, First Monday.

[54]  G. Marcus.  Emotions and politics: hot cognitions and the rediscovery of passion , 1991 .

[55]  C. Loomis.  Political and occupational cleavages in a Hanoverian village, Germany : a sociometric study , 1946 .

[56]  Robert E. Kraut,et al.  Predicting Continued Participation in Newsgroups , 2006, J. Comput. Mediat. Commun..

[57]  D. Knoke.  Networks of Political Action: Toward Theory Construction , 1990 .

[58]  Athayde Ribeiro da Silva.  Psychopathology and Politics , 1963 .

[59]  J. Hornikx.  The SAGE Handbook of persuasion , 2013 .