Politics of Authoritarianism

With the proliferation of social media, authoritarian regimes have found new ways to respond to political unrest. CSMaP examines the different ways these governments have adapted to the digital age to suppress, or spread, narratives online.

Academic Research

  • Working Paper

    The Partisan Effects of Social Media Bans

    Working Paper, March 2026

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    What happens to information environments when democracies ban social media platforms? While a large literature examines information control under authoritarianism, democratic governments have increasingly intervened in major online platforms. We study a prominent case: Brazil’s 2024 national ban on the social media platform X. Using an event-study design, we estimate the causal effects of the ban and examine how partisan identity shaped responses. Drawing on a large sample of politically engaged users and ideal-point estimates of ideology, we find strong partisan asymmetries. Conservative users not aligned with the government were more likely to circumvent the ban, and right-leaning news domains became markedly more prevalent on the platform. We describe this dynamic as a “sorting ratchet”: the ban segmented the digital public sphere along partisan lines, with effects that persisted even after restrictions were lifted. Platform bans in democratic settings may therefore deepen polarization and durably reshape information environments

  • Journal Article

    Why Botter: How Pro-Government Bots Fight Opposition in Russia

    American Political Science Review, 2022

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    There is abundant anecdotal evidence that nondemocratic regimes are harnessing new digital technologies known as social media bots to facilitate policy goals. However, few previous attempts have been made to systematically analyze the use of bots that are aimed at a domestic audience in autocratic regimes. We develop two alternative theoretical frameworks for predicting the use of pro-regime bots: one which focuses on bot deployment in response to offline protest and the other in response to online protest. We then test the empirical implications of these frameworks with an original collection of Twitter data generated by Russian pro-government bots. We find that the online opposition activities produce stronger reactions from bots than offline protests. Our results provide a lower bound on the effects of bots on the Russian Twittersphere and highlight the importance of bot detection for the study of political communication on social media in nondemocratic regimes.

    Date Posted

    Feb 21, 2022

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