We study the effect of Facebook and Instagram access on political beliefs, attitudes, and behavior by randomizing a subset of 19,857 Facebook users and 15,585 Instagram users to deactivate their accounts for 6 wk before the 2020 U.S. election. We report four key findings. First, both Facebook and Instagram deactivation reduced an index of political participation (driven mainly by reduced participation online). Second, Facebook deactivation had no significant effect on an index of knowledge, but secondary analyses suggest that it reduced knowledge of general news while possibly also decreasing belief in misinformation circulating online. Third, Facebook deactivation may have reduced self-reported net votes for Trump, though this effect does not meet our preregistered significance threshold. Finally, the effects of both Facebook and Instagram deactivation on affective and issue polarization, perceived legitimacy of the election, candidate favorability, and voter turnout were all precisely estimated and close to zero.

What happens to international media reporting when governments expel foreign journalists? Countries around the world expel foreign reporters, yet there is no consensus about the effects of such expulsions. We argue there are three possible outcomes of expulsion: a chilling effect, resilience, and backlash. Using China as a case study, we evaluate these competing theories by collecting a novel dataset of foreign news stories about China and applying time-series causal inference methods to measure the effects of expulsion on information origination, composition, and reach after March 2020, when the Chinese government expelled a large number of foreign correspondents. Results show that expelled media organizations did not experience a chilling effect or backlash on reporting and may have changed their production processes to account for expulsion. These findings suggest that news organizations can remain resilient to the impact of extraordinary events which target the organization and disrupt internal production processes.

Social media’s pivotal role in catalyzing social movements is widely acknowledged across scientific disciplines. Past research has predominantly explored social media’s ability to instigate initial mobilization while leaving the question of its capacity to sustain these movements relatively uncharted. This study investigates the persistence of movement activity on Twitter and Gab following a substantial on-the-ground mobilization event catalyzed by social media—the StoptheSteal movement culminating in the January 6th Capitol attack. Our findings indicate that the online communities active in the January 6 mobilization did not display substantial remobilization in the subsequent year. These results highlight the fact that further exploration is needed to understand the factors shaping how and when movements are sustained by social media. In this regard, our study provides valuable insights for scientists across diverse disciplines, on how certain social media platforms may contribute to the evolving dynamics of collective action.

When autocrats do not impose explicit rules of behavior on their subjects, what does political compliance look like? Existing research suggests that such conditions generate uncertainty, leading risk-adverse individuals to self- censor in an effort to minimize the risk of punishment. In this paper, we find that women and men differ in how they express political compliance under conditions of uncertainty. Focusing on Confucius Institute teachers who are given broad objectives but no specific rules of political behavior, we use interviews, a global survey, and an experiment to show that women express compliance by increasing uncensored discussions to persuade host country students toward the Chinese regime’s point of view. In contrast, men comply by vociferously defending the party line and censoring further discussions. These gendered strategies of political compliance are rooted in the differing gender socialization experiences of men and women, who face divergent expectations on how they should interact with others.

Many critics raise concerns about the prevalence of ‘echo chambers’ on social media and their potential role in increasing political polarization. However, the lack of available data and the challenges of conducting large-scale field experiments have made it difficult to assess the scope of the problem1,2. Here we present data from 2020 for the entire population of active adult Facebook users in the USA showing that content from ‘like-minded’ sources constitutes the majority of what people see on the platform, although political information and news represent only a small fraction of these exposures. To evaluate a potential response to concerns about the effects of echo chambers, we conducted a multi-wave field experiment on Facebook among 23,377 users for whom we reduced exposure to content from like-minded sources during the 2020 US presidential election by about one-third. We found that the intervention increased their exposure to content from cross-cutting sources and decreased exposure to uncivil language, but had no measurable effects on eight preregistered attitudinal measures such as affective polarization, ideological extremity, candidate evaluations and belief in false claims. These precisely estimated results suggest that although exposure to content from like-minded sources on social media is common, reducing its prevalence during the 2020 US presidential election did not correspondingly reduce polarization in beliefs or attitudes.

Does Facebook enable ideological segregation in political news consumption? We analyzed exposure to news during the US 2020 election using aggregated data for 208 million US Facebook users. We compared the inventory of all political news that users could have seen in their feeds with the information that they saw (after algorithmic curation) and the information with which they engaged. We show that (i) ideological segregation is high and increases as we shift from potential exposure to actual exposure to engagement; (ii) there is an asymmetry between conservative and liberal audiences, with a substantial corner of the news ecosystem consumed exclusively by conservatives; and (iii) most misinformation, as identified by Meta’s Third-Party Fact-Checking Program, exists within this homogeneously conservative corner, which has no equivalent on the liberal side. Sources favored by conservative audiences were more prevalent on Facebook’s news ecosystem than those favored by liberals.

How do state-controlled broadcasters reach foreign publics to engage in public diplomacy in the era of social media? Previous research suggests that features unique to social media, such as the ability to engage in two-way communication with audiences, provide state-controlled broadcasters new opportunities for online public diplomacy. In this paper, we examine what strategies were used by four Chinese state-controlled media outlets on Twitter to reach foreign publics as the Chinese Communist Party worked to expand its public diplomacy and international media outreach efforts. We find that all outlets increased the volume and diversity of content while none engaged in interactive, two-way communication with audiences, and none appeared to artificially inflate their follower count. One outlet, China Global Television Network, made outsized gains in followership, and it differs from the other Chinese outlets in that it was rebranded, it disseminated a relatively lower share of government-mandated narratives pertaining to China, and the tone of its reporting was more negative. These results show that during a period when Chinese state-controlled broadcasters gained followers on Twitter, outlets made limited use of features unique to social media and instead primarily used social media as a broadcast channel.

We studied the effects of exposure to reshared content on Facebook during the 2020 US election by assigning a random set of consenting, US-based users to feeds that did not contain any reshares over a 3-month period. We find that removing reshared content substantially decreases the amount of political news, including content from untrustworthy sources, to which users are exposed; decreases overall clicks and reactions; and reduces partisan news clicks. Further, we observe that removing reshared content produces clear decreases in news knowledge within the sample, although there is some uncertainty about how this would generalize to all users. Contrary to expectations, the treatment does not significantly affect political polarization or any measure of individual-level political attitudes.

We investigated the effects of Facebook’s and Instagram’s feed algorithms during the 2020 US election. We assigned a sample of consenting users to reverse-chronologically-ordered feeds instead of the default algorithms. Moving users out of algorithmic feeds substantially decreased the time they spent on the platforms and their activity. The chronological feed also affected exposure to content: The amount of political and untrustworthy content they saw increased on both platforms, the amount of content classified as uncivil or containing slur words they saw decreased on Facebook, and the amount of content from moderate friends and sources with ideologically mixed audiences they saw increased on Facebook. Despite these substantial changes in users’ on-platform experience, the chronological feed did not significantly alter levels of issue polarization, affective polarization, political knowledge, or other key attitudes during the 3-month study period.

Social media companies have come under increasing pressure to remove misinformation from their platforms, but partisan disagreements over what should be removed have stymied efforts to deal with misinformation in the United States. Current explanations for these disagreements center on the “fact gap”—differences in perceptions about what is misinformation. We argue that partisan differences could also be due to “party promotion”—a desire to leave misinformation online that promotes one’s own party—or a “preference gap”— differences in internalized preferences about whether misinformation should be removed. Through an experiment where respondents are shown false headlines aligned with their own or the opposing party, we find some evidence of party promotion among Democrats and strong evidence of a preference gap between Democrats and Republicans. Even when Republicans agree that content is false, they are half as likely as Democrats to say that the content should be removed and more than twice as likely to consider removal as censorship.

Repression research examines the causes and consequences of actions or policies that are meant to, or actually do, raise the costs of activism, protest, and/or social movement activity. The rise of digital and social media has brought substantial increases in attention to the repression of digital activists and movements and/or to the use of digital tools in repression, which is spread across many disciplines and areas of study. We organize and review this growing welter of research under the concept of digital repression by expanding a typology that distinguishes actions based on actor type, whether actions are overt or covert, and whether behaviors are shaped by coercion or channeling. This delineation between broadly different forms of digital repression allows researchers to develop expectations about digital repression, better understand what is “new” about digital repression in terms of ex- planatory factors, and better understand the consequences of digital repression.

Government censorship—internet shutdowns, blockages, firewalls—impose signifi- cant barriers to the transnational flow of information despite the connective power of digital technologies. In this paper, we examine whether and how informa- tion flows across borders despite government censorship. We develop a semi-auto- mated system that combines deep learning and human annotation to find co- occurring content across different social media platforms and languages. We use this system to detect co-occurring content between Twitter and Sina Weibo as Covid-19 spread globally, and we conduct in-depth investigations of co-occurring con- tent to identify those that constitute an inflow of information from the global infor- mation ecosystem into China. We find that approximately one-fourth of content with relevance for China that gains widespread public attention on Twitter makes its way to Weibo. Unsurprisingly, Chinese state-controlled media and commercialized domestic media play a dominant role in facilitating these inflows of information. However, we find that Weibo users without traditional media or government affilia- tions are also an important mechanism for transmitting information into China. These results imply that while censorship combined with media control provide substantial leeway for the government to set the agenda, social media provides opportunities for non-institutional actors to influence the information environment. Methodologically, the system we develop offers a new approach for the quantitative analysis of cross- platform and cross-lingual communication.

Research shows that government-controlled media is an effective tool for authoritarian regimes to shape public opinion. Does government-controlled media remain effective when it is required to support changes in positions that autocrats take on issues? Existing theories do not provide a clear answer to this question, but we often observe authoritarian governments using government media to frame policies in new ways when significant changes in policy positions are required. By conducting an experiment that exposes respondents to government-controlled media—in the form of TV news segments—on issues where the regime substantially changed its policy positions, we find that by framing the same issue differently, government-controlled media moves respondents to adopt policy positions closer to the ones espoused by the regime regardless of individual predisposition. This result holds for domestic and foreign policy issues, for direct and composite measures of attitudes, and persists up to 48 hours after exposure.

China after Mao is typically characterized as a country where economic opportunities are based on merit instead of ideological conformity. However, the salience of ideology has grown under the rule of Xi Jinping. Using a large-scale resume audit experiment and a conjoint survey experiment of hiring managers in China, we find that firms in China do not reward job candidates for expressing conformity to the ideol- ogy of the regime, but job candidates who express support for Western democracy are less employable. Results suggest that firms in innovative industries designated as strategically important by the Chinese regime (e.g., artificial intelligence) penalize support for Western democracy by the largest magnitude while the remaining firms in innovative industries do not penalize political non-conformity.

As audiences have moved to digital media, so too have authoritarian regimes. While previous research has focused on how authoritarian regimes employ strategies such as the use of fabricated accounts and content to boost their reach, this paper reveals two different tactics the Chinese regime uses on Douyin, the Chinese version of the video-sharing platform TikTok, to compete for audience attention. We use a multi-modal approach that combines analysis of video, text, and meta-data to examine a novel dataset of Douyin videos. We find that a large share of trending videos are produced by accounts affiliated with the Chinese regime. These videos contain visual characteristics designed to maximize attention such as high levels of brightness and entropy and very short duration, and are more visually similar to content produced by celebrities and ordinary users than to content from non-official media accounts. We also find that the majority of videos produced by regime-affiliated accounts do not fit traditional definitions of propaganda but rather contain stories and topics unrelated to any aspect of the government, the Chinese Communist Party, policies, or politics.

The fast-growing body of research on internet censorship has examined the effects of censoring selective pieces of political information and the unintended consequences of censorship of entertainment. However, we know very little about the broader consequences of coarse censorship or censorship that affects a large array of information such as an entire website or search engine. In this study, we use China’s complete block of Chinese language Wikipedia (zh.wikipedia.org) on May 19, 2015, to disaggregate the effects of coarse censorship on proactive consumption of information—information users seek out—and on incidental consumption of information—information users are not actively seeking but consume when they happen to come across it. We quantify the effects of censorship of Wikipedia not only on proactive information consumption but also on opportunities for exploration and incidental consumption of information. We find that users from mainland China were much more likely to consume information on Wikipedia about politics and history incidentally rather than proactively, suggesting that the effects of censorship on incidental information access may be politically significant.

Saudi Arabia has imprisoned and tortured activists, religious leaders, and journalists for voicing dissent online. This reflects a growing worldwide trend in the use of physical repression to censor online speech. In this paper, we systematically examine the consequences of imprisoning well-known Saudis for online dissent by analyzing over 300 million tweets as well as detailed Google search data from 2010 to 2017 using automated text analysis and crowd-sourced human evaluation of content. We find that repression deterred imprisoned Saudis from continuing to dissent online. However, it did not suppress dissent overall. Twitter followers of the imprisoned Saudis engaged in more online dissent, including criticizing the ruling family and calling for regime change. Repression drew public attention to arrested Saudis and their causes, and other prominent figures in Saudi Arabia were not deterred by the repression of their peers and continued to dissent online.

The proliferation of social media and digital technologies has made it necessary for govern- ments to expand their focus beyond propaganda content in order to disseminate propaganda effectively. We identify a strategy of using clickbait to increase the visibility of political pro- paganda. We show that such a strategy is used across China by combining ethnography with a computational analysis of a novel dataset of the titles of 197,303 propaganda posts made by 213 Chinese city-level governments on WeChat. We find that Chinese propagandists face intense pressures to demonstrate their effectiveness on social media because their work is heavily quantified—measured, analyzed, and ranked—with metrics such as views and likes. Propagandists use both clickbait and non-propaganda content (e.g., lifestyle tips) to capture clicks, but rely more heavily on clickbait because it does not decrease space available for political propaganda. Government propagandists use clickbait at a rate commensurate with commercial and celebrity social media accounts. The use of clickbait is associated with more views and likes, as well as greater reach of government propaganda outlets and messages. These results reveal how the advertising-based business model and affordances of social me- dia influence political propaganda and how government strategies to control information are moving beyond censorship, propaganda, and disinformation.

Protest event analysis is an important method for the study of collective action and social movements and typically draws on traditional media reports as the data source. We introduce collective action from social media (CASM)—a system that uses convolutional neural networks on image data and recurrent neural networks with long short-term memory on text data in a two-stage classifier to identify social media posts about offline collective action. We implement CASM on Chinese social media data and identify more than 100,000 collective action events from 2010 to 2017 (CASM-China). We evaluate the performance of CASM through cross-validation, out-of-sample validation, and comparisons with other protest data sets. We assess the effect of online censorship and find it does not substantially limit our identification of events. Compared to other protest data sets, CASM-China identifies relatively more rural, land-related protests and relatively few collective action events related to ethnic and religious conflict.

A prerequisite for the durability of authoritarian regimes as well as their effective governance is the regime’s ability to gather reliable information about the actions of lower-tier officials. Allowing public participation in the form of online complaints is one approach authoritarian regimes have taken to improve monitoring of lower-tier officials. In this paper, we gain rare access to internal communications between a monitoring agency and upper-level officials in China. We show that citizen grievances posted publicly online that contain complaints of corruption are systematically concealed from upper-level authorities when they implicate lower-tier officials or associates connected to lower-tier officials through patronage ties. Information manipulation occurs primarily through omission of wrongdoing rather than censorship or falsification, suggesting that even in the digital age, in a highly determined and capable regime where reports of corruption are actively and publicly voiced, monitoring the behavior of regime agents remains a challenge.

The study of ideology in authoritarian regimes—of how public preferences are configured and constrained—has received relatively little scholarly attention. Using data from a large-scale online survey, we study ideology in China. We find that public preferences are weakly constrained, and the configuration of preferences is multidimensional, but the latent traits of these dimensions are highly correlated. Those who prefer authoritarian rule are more likely to support nationalism, state intervention in the economy, and traditional social values; those who prefer democratic institutions and values are more likely to support market reforms but less likely to be nationalistic and less likely to support traditional social values. This latter set of preferences appears more in provinces with higher levels of development and among wealthier and better-educated respondents. These findings suggest that preferences are not simply split along a pro-regime or anti-regime cleavage and indicate a possible link between China’s economic reform and ideology.

The Chinese regime has launched a number of online government transparency initiatives to increase the volume of publicly available information about the activities of lower level governments. By analyzing online content produced by local government officials to fulfill these transparency requirements—a random sample of 1.92 million county-level government web pages—this paper shows how websites are commandeered by local-level officials to construct their public image. The majority of content on government websites emphasizes either the competence or benevolence of county executives, depending on where leaders are in the political tenure cycle. Early tenure county executives project images of benevolence by emphasizing their attentiveness and concern toward citizens. Late tenure executives project images of competence by highlighting their achievements. These findings shift the nature of debates concerning the role of the Internet in authoritarian regimes from a focus on regime-society interactions to an examination of dynamics among regime insiders. By focusing on communication and the flow of information between upper-level leaders and lower-level regime agents, this paper reveals how the Internet becomes a vehicle of self-promotion for local politicians.

Xi Jinping’s rise to power in late 2012 has brought political change to China, but the precise nature of shifts remains unclear. In this paper, we evaluate whether the perceived changes associated with Xi Jinping’s rise—increased personalization of power, centralization of authority, party dominance, anti-Western sentiment—are reflected in provincial-level official media. As past research makes clear, media in China have strong signaling functions, and media coverage patterns reveal which actors are up and down in politics. Using innovations in automated text analysis on several million newspaper articles, we identify and tabulate in a comprehensive fashion the individuals and organizations appearing in official media to answer unresolved questions about political shifts in the Xi Jinping era. We find substantively mixed and regionally varied trends in media coverage of political actors that qualify our picture of China’s “new normal.” Provincial media coverage reflects modest increases in the personalization and centralization of political authority, but we find a drop in the media profile of party organizations, and see uneven declines in the media presence of foreign actors. More generally, we highlight marked variation across provinces in coverage trends.

The Chinese government has long been suspected of hiring as many as 2 million people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social media posts, as if they were the genuine opinions of ordinary people. Many academics, and most journalists and activists, claim that these so-called 50c party posts vociferously argue for the government’s side in political and policy debates. As we show, this is also true of most posts openly accused on social media of being 50c. Yet almost no systematic empirical evidence exists for this claim or, more importantly, for the Chinese regime’s strategic objective in pursuing this activity. In the first large-scale empirical analysis of this operation, we show how to identify the secretive authors of these posts, the posts written by them, and their content. We estimate that the government fabricates and posts about 448 million social media comments a year. In contrast to prior claims, we show that the Chinese regime’s strategy is to avoid arguing with skeptics of the party and the government, and to not even discuss controversial issues. We show that the goal of this massive secretive operation is instead to distract the public and change the subject, as most of these posts involve cheerleading for China, the revolutionary history of the Communist Party, or other symbols of the regime. We discuss how these results fit with what is known about the Chinese censorship program and suggest how they may change our broader theoretical understanding of “common knowledge” and information control in authoritarian regimes.

There is ongoing debate over whether authoritarian regimes can maintain control over information given the rise of social media and the Internet. In this debate, China is often cited as a prime example of how authoritarian regimes can retain control, but to date, there has been limited research on whether China’s online censorship strategies can be replicated in other authoritarian regimes. This article shows that China’s ability to censor social media rests on the dominance of domestic firms in China’s market for Internet content. The absence of U.S. social media firms in China allows the Chinese government to engage in censorship through content removal, which can quickly and effectively suppress information. In contrast, for most other regimes, the market for social media is dominated by U.S. multinational firms, e.g., Facebook, YouTube, Twitter, and in these contexts, content removal is an immense challenge. This article then examines the prospects of instituting content removal by developing domestic social media or importing Chinese platforms, and finds that most authoritarian regimes are unlikely to be able to duplicate China’s online censorship efforts.

An increasing number of scholars have established that authoritarian regimes employ quasi-democratic institutions as part of their efforts to retain power. However, we know little about the potential variation among institutions providing citizens with opportunities for voice and the conditions under which such institutions are true channels of responsiveness. In this article, we develop and test the concept of “receptivity,” that is, whether autocrats are willing to incorporate citizen preferences into policy, using a list experiment of 1,377 provincial-and city-level leaders in China. Contrary to expectation, we find that leaders are similarly receptive to citizen suggestions obtained through either formal institutions or the Internet unless they perceive antagonism between the state and citizens, in which case receptivity to input from the Internet declines, while receptivity to formal institutions remains unchanged. Our findings show that whether quasi-democratic institutions are mere window dressing or true channels of responsiveness depends on the perceived quality of state–society relations.

A growing body of research suggests that authoritarian regimes are responsive to societal actors, but our understanding of the sources of authoritarian responsiveness remains limited because of the challenges of measurement and causal identification. By conducting an online field experiment among 2,103 Chinese counties, we examine factors that affect officials’ incentives to respond to citizens in an authoritarian context. At baseline, we find that approximately one-third of county governments respond to citizen demands expressed online. Threats of collective action and threats of tattling to upper levels of government cause county governments to be considerably more responsive, whereas identifying as loyal, long-standing members of the Chinese Communist Party does not increase responsiveness. Moreover, we find that threats of collective action make local officials more publicly responsive. Together, these results demonstrate that top-down mechanisms of oversight as well as bottom-up societal pressures are possible sources of authoritarian responsiveness.

No! Formal Theory, Causal Inference, and Big Data Are Not Contradictory Trends in Political Science

Existing research on the extensive Chinese censorship organization uses observational methods with well-known limitations. We conducted the first large-scale experimental study of censorship by creating accounts on numerous social media sites, randomly submitting different texts, and observing from a worldwide network of computers which texts were censored and which were not. We also supplemented interviews with confidential sources by creating our own social media site, contracting with Chinese firms to install the same censoring technologies as existing sites, and—with their software, documentation, and even customer support—reverse-engineering how it all works. Our results offer rigorous support for the recent hypothesis that criticisms of the state, its leaders, and their policies are published, whereas posts about real-world events with collective action potential are censored.

We offer the first large scale, multiple source analysis of the outcome of what may be the most extensive effort to selectively censor human expression ever implemented. To do this, we have devised a system to locate, download, and analyze the content of millions of social media posts originating from nearly 1,400 different social media services all over China before the Chinese government is able to find, evaluate, and censor (i.e., remove from the Internet) the subset they deem objectionable. Using modern computer-assisted text analytic methods that we adapt to and validate in the Chinese language, we compare the substantive content of posts censored to those not censored over time in each of 85 topic areas. Contrary to previous understandings, posts with negative, even vitriolic, criticism of the state, its leaders, and its policies are not more likely to be censored. Instead, we show that the censorship program is aimed at curtailing collective action by silencing comments that represent, reinforce, or spur social mobilization, regardless of content. Censorship is oriented toward attempting to forestall collective activities that are occurring now or may occur in the future—and, as such, seem to clearly expose government intent.