Abstract: Successful use of bots and trolls as tools of its expansionist foreign policy demonstrated the Russian government's superior capability in computational propaganda. Yet the main area of application for these tools remains inside Russia: to prop up Vladimir Putin's approval ratings and deny his opponents an opportunity to reach potential voters. In this paper, we use supervised machine learning algorithms for bot detection and sentiment analysis to do a first systematic survey of bot activity in the Russian segment of Twitter. We discover a high yet fluctuating volume of bot communication and presence of both pro- and anti-government as well as neutral bots. We also identify sources of information they spread and formulate testable hypotheses about the political strategy behind bots deployment. Finally, we discuss the implications of autocrats' reliance on domestic computational propaganda for the response to their activities abroad.
Speaker's Biography: Sergey Sanovich received his Ph.D. in Politics at NYU. He studies how autocrats use the power of persuasion to come to, and stay in, office. His ongoing research is focused on online censorship and propaganda by authoritarian regimes; elections and partisanship in electoral autocracies; and personalization of politics in both autocratic and democratic countries. To conduct his research, Sergey collects big data from social media, digitalizes archival documents, and runs field and survey experiments both online and offline.