Abstract
The 2015–2017 Russian Internet Research Agency (IRA)’s coordinated information operation is one of the earliest and most studied of the social media age. A set of 38 city-specific inauthentic “newsfeeds” made up a large, underanalyzed part of its English-language output. We label 1,000 tweets from the IRA newsfeeds and a matched set of real news sources from those same cities with up to five labels indicating the tweet represents a world in unrest and, if so, of what sort. We train a natural language classifier to extend these labels to 268 k IRA tweets and 1.13 million control tweets. Compared to the controls, tweets from the IRA were 34% more likely to represent unrest, especially crime and identity danger, and this difference jumped to about twice as likely in the months immediately before the election. Agenda setting by media is well-known and well-studied, but this weaponization by a coordinated information operation is novel.
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