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.

Debates around the effectiveness of high-profile Twitter account suspensions and similar bans on abusive users across social media platforms abound. Yet we know little about the effectiveness of warning a user about the possibility of suspending their account as opposed to outright suspensions in reducing hate speech. With a pre-registered experiment, we provide causal evidence that a warning message can reduce the use of hateful language on Twitter, at least in the short term. We design our messages based on the literature on deterrence, and test versions that emphasize the legitimacy of the sender, the credibility of the message, and the costliness of being suspended. We find that the act of warning a user of the potential consequences of their behavior can significantly reduce their hateful language for one week. We also find that warning messages that aim to appear legitimate in the eyes of the target user seem to be the most effective. In light of these findings, we consider the policy implications of platforms adopting a more aggressive approach to warning users that their accounts may be suspended as a tool for reducing hateful speech online.

Do online social networks affect political tolerance in the highly polarized climate of postcoup Egypt? Taking advantage of the real-time networked structure of Twitter data, the authors find that not only is greater network diversity associated with lower levels of intolerance, but also that longer exposure to a diverse network is linked to less expression of intolerance over time. The authors find that this relationship persists in both elite and non-elite diverse networks. Exploring the mechanisms by which network diversity might affect tolerance, the authors offer suggestive evidence that social norms in online networks may shape individuals’ propensity to publicly express intolerant attitudes. The findings contribute to the political tolerance literature and enrich the ongoing debate over the relationship between online echo chambers and political attitudes and behavior by providing new insights from a repressive authoritarian context.

“Clickbait” media has long been espoused as an unfortunate consequence of the rise of digital journalism. But little is known about why readers choose to read clickbait stories. Is it merely curiosity, or might voters think such stories are more likely to provide useful information? We conduct a survey experiment in Italy, where a major political party enthusiastically embraced the esthetics of new media and encouraged their supporters to distrust legacy outlets in favor of online news. We offer respondents a monetary incentive for correct answers to manipulate the relative salience of the motivation for accurate information. This incentive increases differences in the preference for clickbait; older and less educated subjects become even more likely to opt to read a story with a clickbait headline when the incentive to produce a factually correct answer is higher. Our model suggests that a politically relevant subset of the population prefers Clickbait Media because they trust it more.

Does social media educate voters, or mislead them? This study measures changes in political knowledge among a panel of voters surveyed during the 2015 UK general election campaign while monitoring the political information to which they were exposed on the Twitter social media platform. The study's panel design permits identification of the effect of information exposure on changes in political knowledge. Twitter use led to higher levels of knowledge about politics and public affairs, as information from news media improved knowledge of politically relevant facts, and messages sent by political parties increased knowledge of party platforms. But in a troubling demonstration of campaigns' ability to manipulate knowledge, messages from the parties also shifted voters' assessments of the economy and immigration in directions favorable to the parties' platforms, leaving some voters with beliefs further from the truth at the end of the campaign than they were at its beginning.

A growing body of research explores the factors that affect when corrupt politicians are held accountable by voters. Most studies, however, focus on one or few factors in isolation, leaving incomplete our understanding of whether they condition each other. To address this, we embedded rich conjoint candidate choice experiments into surveys in Argentina, Chile, and Uruguay. We test the importance of two contextual factors thought to mitigate voters’ punishment of corrupt politicians: how widespread corruption is and whether it brings side benefits. Like other scholars, we find that corruption decreases candidate support substantially. But, we also find that information that corruption is widespread does not lessen the sanction applied against corruption, whereas information about the side benefits from corruption does, and does so to a similar degree as the mitigating role of permissible attitudes toward bribery. Moreover, those who stand to gain from these side benefits are less likely to sanction corruption.

Michael Jordan supposedly justified his decision to stay out of politics by noting that Republicans buy sneakers too. In the social media era, the name of the game for celebrities is engagement with fans. So why then do celebrities risk talking about politics on social media, which is likely to antagonize a portion of their fan base? With this question in mind, we analyze approximately 220,000 tweets from 83 celebrities who chose to endorse a presidential candidate in the 2016 U.S. presidential election campaign to assess whether there is a cost—defined in terms of engagement on Twitter—for celebrities who discuss presidential candidates. We also examine whether celebrities behave similarly to other campaign surrogates in being more likely to take on the “attack dog” role by going negative more often than going positive. More specifically, we document how often celebrities of distinct political preferences tweet about Donald Trump, Bernie Sanders, and Hillary Clinton, and we show that followers of opinionated celebrities do not withhold engagement when entertainers become politically mobilized and do indeed often go negative. Interestingly, in some cases political content from celebrities actually turns out to be more popular than typical lifestyle tweets.