"Online Reactions to the 2017 ‘Unite the Right’ Rally in Charlottesville: Measuring Polarization in Twitter Networks Using Media Followership"

A new paper of mine came out in final form a few days ago. Here are some details.

Title: Online Reactions to the 2017 ‘Unite the Right’ Rally in Charlottesville: Measuring Polarization in Twitter Networks Using Media Followership

Authors: Joseph H. Tien, Marisa C. Eisenberg, Sarah T. Cherng, and Mason A. Porter

Abstract: Network analysis of social media provides an important new lens on politics, communication, and their interactions. This lens is particularly prominent in fast-moving events, such as conversations and action in political rallies and the use of social media by extremist groups to spread their message. We study the Twitter conversation following the August 2017 ‘Unite the Right’ rally in Charlottesville, Virginia, USA using tools from network analysis and data science. We use media followership on Twitter and principal component analysis (PCA) to compute a ‘Left’/‘Right’ media score on a one-dimensional axis to characterize Twitter accounts. We then use these scores, in concert with retweet relationships, to examine the structure of a retweet network of approximately 300,000 accounts that communicated with the #Charlottesville hashtag. The retweet network is sharply polarized, with an assortativity coefficient of 0.8 with respect to the sign of the media PCA score. Community detection using two approaches, a Louvain method and InfoMap, yields communities that tend to be homogeneous in terms of Left/Right node composition. We also examine centrality measures and find that hyperlink-induced topic search (HITS) identifies many more hubs on the Left than on the Right. When comparing tweet content, we find that tweets about ‘Trump’ were widespread in both the Left and Right, although the accompanying language (i.e., critical on the Left, but supportive on the Right) was unsurprisingly different. Nodes with large degrees in communities on the Left include accounts that are associated with disparate areas, including activism, business, arts and entertainment, media, and politics. By contrast, support of Donald Trump was a common thread among the Right communities, connecting communities with accounts that reference white-supremacist hate symbols, communities with influential personalities in the alt-right, and the largest Right community (which includes the Twitter account FoxNews).

Note: And only now after several rounds of page proofs, right after it's too late, do I notice that the typesetters changed "Right" to "right" in the paper title, even though it is a proper noun. Well, we had plenty of chances to notice this typo that they introduced, so it's frustrating that this is another one of those that I notice immediately as soon as it's published (while not catching it in my numerous chances to see it).