Partisan alignments and political polarization online

Abstract

With the advent of Twitter and the ability to collect large datasets from this technology, researchers have the opportunity to analyze political participation in cross-national electoral contexts. This paper capitalizes on this capability to examine political polarization and citizen engagement during the US and French presidential campaigns. We use the Twitter Gardenhose collection to filter tweets based on keywords around a 50-day windowrespectively. From these data, we constructed partisan alignments based on hashtag usage and retweet networks. We found evidence of more stark political polarization in the French case, while the US case demonstrated less partisan division. This study elaborates commonalities and contrasts in the use of a major social medium by citizens in contexts that differ in political culture and language but feature similar ideological divides, electoral politics, and campaign contexts. We conclude by discussing the implications of computational social science and "big data" in communications, comparative politics, and political sociology.

Influencing Myself: Self-Reinforcement Through Online Political Expression

“…On the other hand, there is considerable disagreement about the extent of partisan selectivity and ideological segregation in online political discourse. A number of studies have found no evidence of such ideological segregation (Hanna et al, 2013) or even that discussion heterogeneity does take place in online discussion platforms (Kelly, Fisher, & Smith, 2006; Lee, Choi, Kim, & Kim, 2014). Kelly et al (2006), for example, found that participants in Usenet discussion newsgroups often engage in discussion with others holding different political views.…”

Analyzing Political Communication with Digital Trace Data

“…It has repeatedly been shown that the volume of messages referring to politics rises significantly during mediated events (e.g. Burgess and Bruns 2012;Hanna et al 2013;Trilling 2014) and that users change their behavior-for instance by posting more messages containing comments on the shared experience and less containing interactions with other users (e.g. Jungherr 2014a; Trilling 2014).…”

Quantifying echo chamber effects in information spreading over political communication networks

“…That is, individuals prefer to interact with other individuals who are similar to them, or share the same views and orientations [4][5][6]. Homophily leads to a natural polarization of societies into groups with different perspectives, that leave digital fingerprints in the online realm, and provide researchers with large-scale data sets for the study of polarization in different contexts, such as the US and French presidential elections [7], secular vs. Islamist discussions during the 2011 Egyptian revolution [8,9], or the 15M movement of 2011 in Spain [10]. Political orientation, in particular, has been shown to drive the segregation of online communication networks into separated communities [11,12].…”