The proliferation of social media—counter to the initial projection that it would usher in democratization across the globe (Diamond Reference Diamond2010; Tufekci and Wilson Reference Tufekci and Wilson2012)—has recently become a key ingredient in technological innovations that expand autocrats’ toolkits. Social media can be used to facilitate domestic and international goals alike by providing autocrats with platforms for monitoring popular attitudes toward a plethora of issues; interfering in public discussions at scale; reaching out to diverse groups of the population with promises, perks, or threats; collecting information about dissidents; or sowing discord and uncertainty among opponents inside and outside the country (Deibert Reference Deibert2019; Feldstein Reference Feldstein2019; Gunitsky Reference Gunitsky2015; Lorentzen Reference Lorentzen2014; Tucker et al. Reference Tucker, Theocharis, Roberts and Barbera2017). Here we investigate another way that modern nondemocracies employ social media to secure regime survival by analyzing how one competitive authoritarian regime, Russia, uses new artificial intelligence technologies (social media bots) to respond to both offline and online opposition activities.

Although social media trolls and bots are a new phenomena in politics, they have recently gained increasing scholarly attention (Bolsover and Howard Reference Bolsover and Howard2017; King, Pan, and Roberts Reference King, Pan and Roberts2017; Sanovich, Stukal, and Tucker Reference Sanovich, Stukal and Tucker2018; Stukal et al. Reference Stukal, Sanovich, Bonneau and Tucker2017; Tucker et al. Reference Tucker, Theocharis, Roberts and Barbera2017; Wooley Reference Wooley, Persily and Tucker2020), especially due to mounting evidence suggesting that the Russian government has employed them in pursuit of foreign policy goals (Leonnig, Hamburger, and Helderman Reference Leonnig, Hamburger and Helderman2017; Shane Reference Shane2017). Previous research has also shown that human trolls can be employed to spread discord (Golovchenko et al. Reference Golovchenko, Buntain, Eady, Brown and Tucker2020; Linvill et al. Reference Linvill, Boatwright, Grant and Warren2019; Phillips Reference Phillips2015), cause distrust in the political system of autocrats’ international opponents (Badawi, Lerman, and Ferrara Reference Badawi, Lerman and Ferrara2018), spread deceptive content (Lou, Flammini, and Menczer Reference Lou, Flammini and Menczer2019), or disseminate disinformation of various kinds (Shao et al. Reference Shao, Ciampaglia, Varol, Yang, Flammini and Menczer2018; Starbird Reference Starbird2019). Paid human trolls can also be used for domestic purposes in nondemocratic regimes—for example, for spreading positive sentiment toward the regime (King, Pan, and Roberts Reference King, Pan and Roberts2017) or diverting critical online discussions away from politically charged issues (Sobolev Reference Sobolev2018).

However, academic research on the ways authoritarian regimes use social media bots, defined as algorithmically controlled social media accounts, in the context of domestic politics is scarce. This is perhaps due to a lack of data about bots, which is in turn due to numerous challenges that arise when identifying bots, quantifying their behavior, and collecting very large relevant social media datasets. To mitigate this problem, previous research has mostly relied on publicly available general-purpose algorithms for detecting bots. This research has shown that bots can be used to promote human-generated political content (Stella, Ferrara, and Domenico Reference Stella, Ferrara and De Domenico2018) and are even capable of occupying a central role in online political discussions (Schuchard et al. Reference Schuchard, Crooks, Stefanidis, Croitoru, Aiello, Cherifi, Cherifi, Lambiotte, Lió and Rocha2019). Anecdotal evidence suggests that bots are employed to instill doubts about mainstream interpretations of political events or spread conspiracy theories (Kitzie, Karami, and Mohammadi Reference Kitzie, Karami and Mohammadi2018). Other scholarship has focused on evaluating the effect of bots on online network characteristics (Ghosh et al. Reference Ghosh, Viswanath, Kooti, Sharma, Korlam, Benevenuto, Ganguly and Gummadi2012; Zhang et al. Reference Zhang, Zhang, Zhang and Yan2016) or revealing specific strategies employed to manipulate social media algorithms (Benigni, Joseph, and Carley Reference Benigni, Joseph, Carley, Agarwal, Dokoohaki and Tokdemir2019). An alternative strategy of detecting bots has been to develop technologies based on new machine learning algorithms (Chavoshi, Hamooni, and Mueen Reference Chavoshi, Hamooni and Mueen2016; Davis et al. Reference Davis, Varol, Ferrara, Flammini and Menczer2016; Stukal et al. Reference Stukal, Sanovich, Bonneau and Tucker2017), although this body of research has been published outside of political science and has been largely disconnected from political science theories.

Here, we take the research on the political use of social media bots in authoritarian regimes a step further. We build on diverse strands of research about protest movements and authoritarian politics and theorize about the different ways in which political actors in a nondemocratic regime can use social media bots to prevent, suppress, or react to offline and online opposition activities. We choose to focus on the political strategies behind the use of bots in nondemocratic regimes due to the complex and nonlinear effects that social media can have on mass political protests and other types of political instability in authoritarian regimes. Periods of instability, or those leading to instability, are arguably the times when social media platforms can either facilitate activists’ access to broadcasting technologies (Rohlinger and Corrigall-Brown Reference Rohlinger, Corrigall-Brown, Snow, Soule, Kriesi and McCammon2019) or enable the government to manipulate public perception of the factors that are known to matter for protest mobilization, including grievances (Gurney and Tierney Reference Gurney and Tierney1982; Klandermans Reference Klandermans1997; Opp Reference Opp1988; Van Stekelenburg, Klandermans, and Walgrave Reference Van Stekelenburg, Klandermans, Walgrave, Snow, Soule, Kriesi and McCammon2019; Walsh Reference Walsh1981), group political efficacy (Bandura Reference Bandura1997; Finkel Reference Finkel1985; Wallace, Zepeda-Millan, and Jones-Correa Reference Wallace, Zepeda-Millan and Jones-Correa2014), emotions (Halfmann and Young Reference Halfmann and Young2010; Jasper and Poulsen Reference Jasper and Poulsen1995), social esteem (McClendon Reference McClendon2014), or an individual’s cost–benefit calculus (Hardin Reference Hardin1982; Oliver Reference Oliver1993; Olson Reference Olson1965). When this type of manipulation happens during or on the eve of protest rallies, it can be aimed at controlling the information environment and preventing rallies from growing. Alternatively, manipulation can seek to exercise online agenda control (McCombs Reference McCombs2014) in order to prevent the opposition from taking the initiative and dominating online political communications. What these two strategies have in common is that governments today can pursue both of them through the use of automated bots, which remains an understudied topic in political science.

To address this gap in the literature, we develop theory-based predictions about the political strategies behind the use of bots to counter domestic opposition in Russia and empirically test these predictions with a large collection of data on the activity of Russian Twitter bots from 2014 to 2018. We argue that not only government agencies, but also nongovernment actors, can deploy pro-government bots for policy and agency reasons. In both cases, the deployed bots can be focused on either demobilizing opposition supporters offline or exercising online agenda control. We develop observable implications of these two alternatives and empirically show that even though pro-government bots are involved in both types of activities, the ones we are able to identify are primarily employed as an online agenda control tool.

Our contribution is twofold. First, we bridge the gap between scholarship from the field of computer science on bot detection and research in political science on authoritarian politics by reverse-engineering the use of social media bots in a competitive authoritarian setting and identifying specific political strategies that can be pursued with the use of bots. Second, we develop testable hypotheses about the way social media bots can be used to counter domestic opposition activity either online or offline. We derive our hypotheses from diverse strands of political science literature, including previous research on trolls (King, Pan, and Roberts Reference King, Pan and Roberts2017; Roberts Reference Roberts2018), and show that some of those predictions do not hold for bots. Overall, our study advances previous research on the toolkit for undermining online opposition that is available in modern nondemocratic regimes (Sanovich, Stukal, and Tucker Reference Sanovich, Stukal and Tucker2018) by bringing together theoretical predictions and data.

RUSSIAN TWITTER BOTS In this section, we provide some background information about the activity of Twitter bots in Russia by focusing on two questions: What is a Twitter bot? And who could be interested in deploying Twitter bots in contemporary Russia? Readers who are interested in a deeper understanding of the technological details of bot activity or illustrative examples of tweets posted by pro-government bots are referred to Online Appendices B–C. What Is a Twitter Bot? We define Twitter bots as algorithmically controlled accounts that can automatically perform a variety of actions including posting, retweeting, liking, responding, etc. In spite of this simple definition, bots represent very diverse types of social media accounts. In some trivial cases, a bot can be as simple as a small script that redirects updates from a website to someone’s Twitter page. In more sophisticated cases, bots can fully control a Twitter account and even communicate with other social media users (Freitas et al. Reference Freitas, Benevenuto, Ghosh, Veloso, Pei, Silvestri and Tang2015), thus resembling chatbots or recomender systems one could encounter when interacting with a large company online. Here, we focus on the latter case of the more sophisticated computer programs that are capable of maintaining Twitter activity, without a continuing intervention by a human operator. Figure 1 shows an example of such a Twitter bot that adopted the old Russian male name Yermolay as its screen name. Yermolay is a bot that is not hard to identify for a number of reasons. First, this account has posted over 12,000 tweets, but there are only six other Twitter users who follow its tweets. Second, this account does not have a user picture and employs the default silhouette image instead, which is a common sign of a bot (Nimmo Reference Nimmo2017). Additionally, the bio section for this account does not contain any meaningful information and is merely a code snippet. Finally, the tweets posted by this account resemble news headlines, another behavior typical of bots (Sanovich, Stukal, and Tucker Reference Sanovich, Stukal and Tucker2018). Why Deploy Bots in Russia? In recent years, fake social media accounts similar to Yermolay have gained growing popularity in Russia. Bots stand out in the repertoire of digital information manipulation tools for a number of reasons. They are hard to trace, as—unlike humans, who need to work from a physical location, which facilitates tracking their IP addresses and linking them to certain organizations like the Internet Research Agency—bots can be deployed anywhere, including cloud computing environments, digital devices, and appliances (Boulton Reference Boulton2015; Kumar and Lim Reference Kumar and Lim2020). This feature makes bots specifically suitable for covert online operations that are aimed at affecting public opinion. Bots are also automated tools that can be deployed at scale (Hegelich and Janetzko Reference Hegelich and Janetzko2016), which makes them particularly useful for specific tasks including imitating regime support by ordinary citizens or manipulating social media and search engine algorithms to promote specific content online. Last, bots are relatively cheap to employ. Unlike paid human trolls—another novel tool available to autocrats in the digital era—bots typically involve minimal human intervention and do not require salary or overtime payments. Bots are pieces of software that can run online for indefinite periods of time (until they are detected and shut down by the platforms on which they operate, or by their creators) without requiring additional resources besides the initial production costs (Agarwal Reference Agarwal2017; Pickell Reference Pickell2018). The ease of bot deployment partially explains the utility of bots and their observed wide use in autocratic regimes. Although our knowledge of government-sponsored bot deployment initiatives is generally scarce, previous research was relatively successful in identifying the use of bots by Russian authorities at the regional level. In particular, it has been revealed that most regional governors in Russia have official Instagram accounts followed by large numbers of bots, accounting for anywhere from 13% to 63% of governors’ followers (Center for Current Politics 2019). The underlying motivation for making bots follow governors’ accounts remains unknown, but anecdotal evidence suggests two potential explanations. First, the deployment of bots can be motivated by policy-related concerns. A recent example comes from Moscow, where the regional government employed fake social media accounts supporting a controversial housing reconstruction program on the eve of the 2018 Moscow mayoral election (Chizhova Reference Chizhova2017). Abundant evidence also suggests that pro-government bots were employed during the 2019 regional governor elections to promote positive sentiment toward incumbent candidates in a number of Russian regions (Davidov Reference Davidov2019). There are also multiple agency-related reasons for deploying pro-government bots. On the one hand, the Kremlin has required regional governors to pay more attention to their social media activity and has advised them to create regional government departments focused on managing political communication in social media (Antonova Reference Antonova2018). On the other, public employees at these departments often lack the necessary skills for effective social media communication and rely on bots to artificially inflate relevant activity indicators. Agency-related considerations are arguably also involved in the use of bots in the interests of other levels of the Russian government. Politicians and businessmen can deploy pro-regime bots in an effort to signal loyalty or develop stronger ties to the regime, which can result in extra perks and easier access to public resources (Pertsev Reference Pertsev2019). The attractiveness of bots as a loyalty-signaling tool is due to the imbalance of public and private information in nondemocratic settings. Although private actors can use nonpublic communication channels with the government to claim responsibility for bot activity, the difficulty of tracing bots back to their masters creates relatively low risks of popular condemnation or international reputation loss for these private actors. Our analysis in this article remains largely agnostic about specific actors coordinating or funding the bots and bot-nets we analyze, the only assumption being that those actors are interested in maximizing the intended effects of bots on other Twitter users, either for policy-related reasons or due to agency considerations. In the next section, we develop two different but related theoretical frameworks for conceptualizing the political logic behind the use of pro-government Twitter bots by autocratic regimes in their own country’s domestic politics. We focus on bots’ responses to increases in offline or online opposition activity because these periods provide bot managers with a good opportunity to signal loyalty to the regime or justify potential funding requests. Additionally, this focus allows us to link different strands of literature from the fields of comparative politics and political communication to explain a novel phenomenon in the modern politics of authoritarian regimes.

THEORY AND HYPOTHESES Tension between incumbents and the opposition is a—if not the—primary component of domestic politics in competitive authoritarian regimes, whose survival largely depends on the regime’s ability to manage the informational environment (Guriev and Treisman Reference Guriev and Treisman2019) and maintain the widespread belief in low numbers of opposition supporters (Kuran Reference Kuran1991; Lohmann Reference Lohmann1994), their lack of coordination (Kuran and Romero Reference Kuran, Romero, Congleton, Grofman and Voigt2019), and the high expected costs of engagement in opposition activities (Rubin Reference Rubin2014). These goals are often achieved by silencing adverse information and emphasizing positive agendas (Roberts Reference Roberts2018) or selectively attributing good and bad news to the government and other actors, respectively (Rozenas and Stukal Reference Rozenas and Stukal2019). However, the effectiveness of these techniques is questionable in times of large-scale collective actions that can not only pose an immediate threat to political elites but also send broad communities strong antiregime signals, thereby creating and popularizing alternative public agendas. Offline collective action and online political campaigns (for example, high-profile anticorruption investigations targeting senior officials) organized by opposition leaders can therefore motivate nondemocratic regimes to mobilize extra resources and demonstrate the full potential of their propaganda machines in mass and social media. In addition, these are also the times that can provide the managers of social media bots, who are not necessarily affiliated with the government, with a good opportunity to signal their loyalty to the regime. They could also use this opportunity to justify the need for further funding and access to government resources by deploying their networks of social media bots at full scale. Given these considerations and the growing political science literature on the online aspects of offline political mobilization (Aytaç, Schiumerini, and Stokes Reference Aytaç, Schiumerini and Stokes2018; Steinert-Threlkeld Reference Steinert-Threlkeld2017; Sullivan Reference Sullivan2016), we focus on analyzing the political strategies behind the use of pro-government bots in times of both offline and online opposition mobilization to study the differential response of bots to these two types of events. Theoretically, bot responses can be conceptualized in terms of their attempts to change the cost–benefit analysis of a potential opposition supporter weighing the costs and benefits of taking actions in support of the opposition in a competitive authoritarian environment (Kuran Reference Kuran1991; Oliver Reference Oliver1993). One way to push citizens away from getting involved in opposition initiatives is to increase the actual costs of staying informed about opposition activities and plans for collective action. In some countries, including China, this is achieved by large-scale censorship that makes it harder for ordinary people to get access to off-limits information (King, Pan, and Roberts Reference King, Pan and Roberts2017). However, censorship is not the only tool available to nondemocratic regimes. An alternative technique is to increase—rather than decrease via censorship—the volume of available information (Roberts Reference Roberts2018). Swamping news consumers with massive flows of irrelevant information can make it harder and more time consuming to find antiregime news. Alternatively, bots might seek to change the public perception of regime popularity. Under an unpopular government, even a small disorganized rally can stir up popular grievances and spark a cascade of large-scale protests capable of overthrowing the regime. However, the expectations can be dramatically different when there is a widespread belief that the regime enjoys high levels of popular support. Attempting to make the regime and its leaders look stronger and more popular is therefore one way bots could affect the expected costs and benefits of supporting the opposition. Another way for bots to affect the perceived costs of joining opposition activities online or offline is to act as automated trolls that publicly harass and threaten opposition activists, thereby raising additional concerns about the physical security and potential future persecution of opposition supporters. Even though one could argue that actual human trolls might be more effective in arguing with activists and emphasizing weaknesses in their agenda, automated bot accounts could be better at inducing fear via posting a slew of threats to opposition leaders or slandering them at scale—for example, by publicizing compromising information hacked from their email accounts (Sanovich Reference Sanovich, Woolley and Howard2018). Taken together, the goals of decreasing the expected benefits and increasing the expected costs of getting involved in offline or online opposition activities shape the space of possible political strategies available to pro-government bots. Observable Implications and Hypotheses In this paper, we focus on four observable implications for bot behavior during offline protests and increased online opposition activity that we derive from our theoretical cost–benefit analysis framework. One potential strategy that bots can employ is to deemphasize the protest-related agenda by distracting social media users and augmenting informational noise in their social media feeds. As a result of this strategy, if bots are activated—for whatever reason—in times of street protests or online opposition mobilization, then the volume of content posted by pro-government bots should go up during these periods. We refer to this generic observable implication as the volume implication. Another observable implication of the same strategy is to amplify a more diverse set of news. Some of the news might be positive for the regime, others could be neutral or negative but unrelated to the cause of the protest. The goal is to distract social media users, expose them to an information environment that is rich in news of every kind, and make it harder for them to focus on the protest-related agenda (Munger et al. Reference Munger, Bonneau, Nagler and Tucker2018). We thereby expect bots to increase in the diversity of the accounts they retweet as a response to offline or online opposition mobilization, which we refer to as retweet diversity. Another possible strategy for decreasing opposition supporters’ expected benefits is to program bots to adopt the tactics similar to what paid human trolls do in China. As King, Pan, and Roberts (Reference King, Pan and Roberts2017) show, Chinese trolls act as cheerleaders that express positive sentiment about government activities. Bots can post similar content automatically and on a large scale. More specifically, we measure this behavior with the number of tweets that pro-government bots post about Vladimir Putin on a given day. We refer to this response as cheerleading. Finally, the automated trolling and harassment of opposition leaders constitutes an alternative strategy aimed at increasing the expected costs of supporting opposition. We measure the use of this strategy, referred to as negative campaigning, with the number of pro-government bot-produced tweets that mention Alexey Navalny, a prominent Russian opposition leader, who is also known for his charisma and ability to bring large numbers of protesters to the streets (Nechepurenko Reference Nechepurenko2018). These four observable implications provide us with a set of hypotheses that can be tested empirically to both shed light on the logic behind the use of bots in domestic politics in modern nondemocratic regimes and contrast the use of bots during mass street protests and their deployment as a response to opposition mobilization online. Are bots primarily used as yet another tool for demobilizing citizens in times when opposition is trying to bring people onto the streets, or are they mainly employed as an online agenda control, or gatekeeping, mechanism (McCombs and Shaw Reference McCombs and Shaw1972) tailored to regulating information flows on social media? In Table 1, we concisely summarize our hypotheses that are drawn from the two different—but not mutually exclusive—theoretical frameworks for explaining the use of pro-regime political bots in comparative authoritarian regimes. The first is that bots are used in the interest of offline demobilization—that is, to reduce participation in offline protests. The second is that bots are used to control the online agenda, which we refer to as the online agenda control framework, and therefore will be mobilized in response to opposition online activity.Footnote 1 These two theoretical perspectives do not differ in the hypothesized tactics that will be used by pro-government bots but only in the events (offline protest vs. online activity) that will trigger the use of these bots. Thus, in Table 1, the four observable implications that start with H1 (H1a, H1b, H1c, and H1d) are derived from the offline demobilization theoretical framework, whereas the four implications that start with H2 (H2a, H2b, H2c, and H2d) are the predicted empirical observations from the online agenda control theoretical framework.