Itai Himelboim, Sweetser, K.D., Spencer F. Tinkham, Kristen Cameron, (Grady PhD Student)., Danelo, M., & West, K. (2016). Valence-based Homophily on Twitter: Network Analysis of Emotion and Political Talk in the 2012 Presidential Election. New Media & Society, 18(7), 1382–1400. doi: 10.1177/1461444814555096
Abstract: 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.
Abstract: Participants (N=88) in a two-condition (Facebook post information level: high vs. low) mixed factorial design took part in a laboratory experiment that utilized eye tracking to gauge what areas of the page in common news layouts attract viewers’ gaze, and whether this viewing amount of information about the story disclosed in the Facebook posts. […]
Bartosz WojdynskiCamila EspinaKate KeibJennifer MalsonHyejin BangYen-I Lee
A Social Networks Approach to Online Social Movement:
Abstract: The movement to free Al Jazeera journalists (#FreeAJStaff), imprisoned by Egyptian authorities, utilized Twitter over almost two years, between 2014 and 2015. This study applied a social networks approach to study patterns of information flow, social mediators, and clusters, formed by the #FreeAJStaff movement on Twitter.Analysis of 22 months of data found social mediators […]