We study the Twitter conversation following the August 2017 Unite the Right' rally in Charlottesville, Virginia, 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 nodes. 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 largely homogeneous communities in terms of Left/Right node composition. When comparing tweet content, we find that tweets about Trump’ were widespread in both the Left and
Right, though the accompanying language 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. 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).

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