Academic Research

As an academic research institute dedicated to studying how social media impacts politics, policy, and democracy, CSMaP publishes peer-reviewed research in top academic journals and produces rigorous data reports on policy relevant topics.

Search or Filter

  • Working Paper

    To Moderate, Or Not to Moderate: Strategic Domain Sharing by Congressional Campaigns

    Working Paper, April 2022

    View Article View abstract

    We test whether candidates move to the extremes before a primary but then return to the center for the general election to appeal to the different preferences of each electorate. Incumbents are now more vulnerable to primary challenges than ever as social media offers a viable pathway for fundraising and messaging to challengers, while homogeneity of districts has reduced general election competitiveness. To assess candidates' ideological trajectories, we estimate the revealed ideology of 2020 congressional candidates (incumbents, their primary challengers, and open seat candidates) before and after their primaries, using a homophily-based measure of domains shared on Twitter. This method provides temporally granular data to observe changes in communication within a single election campaign cycle. We find that incumbents did move towards extremes for their primaries and back towards the center for the general election, but only when threatened by a well-funded primary challenge, though non-incumbents did not.

    Date Posted

    Apr 05, 2022

  • Journal Article

    Short of Suspension: How Suspension Warnings Can Reduce Hate Speech on Twitter

    Perspectives on Politics, 2021

    View Article View abstract

    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.

    Date Posted

    Nov 22, 2021

  • Journal Article

    Twitter Flagged Donald Trump’s Tweets with Election Misinformation: They Continued to Spread Both On and Off the Platform

    Harvard Kennedy School (HKS) Misinformation Review, 2021

    View Article View abstract

    We analyze the spread of Donald Trump’s tweets that were flagged by Twitter using two intervention strategies—attaching a warning label and blocking engagement with the tweet entirely. We find that while blocking engagement on certain tweets limited their diffusion, messages we examined with warning labels spread further on Twitter than those without labels. Additionally, the messages that had been blocked on Twitter remained popular on Facebook, Instagram, and Reddit, being posted more often and garnering more visibility than messages that had either been labeled by Twitter or received no intervention at all. Taken together, our results emphasize the importance of considering content moderation at the ecosystem level.

  • Journal Article

    Tweeting Beyond Tahrir: Ideological Diversity and Political Intolerance in Egyptian Twitter Networks

    World Politics, 2021

    View Article View abstract

    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.

  • Journal Article

    Trumping Hate on Twitter? Online Hate Speech in the 2016 U.S. Election Campaign and its Aftermath.

    Quarterly Journal of Political Science, 2021

    View Article View abstract

    To what extent did online hate speech and white nationalist rhetoric on Twitter increase over the course of Donald Trump's 2016 presidential election campaign and its immediate aftermath? The prevailing narrative suggests that Trump's political rise — and his unexpected victory — lent legitimacy to and popularized bigoted rhetoric that was once relegated to the dark corners of the Internet. However, our analysis of over 750 million tweets related to the election, in addition to almost 400 million tweets from a random sample of American Twitter users, provides systematic evidence that hate speech did not increase on Twitter over this period. Using both machine-learning-augmented dictionary-based methods and a novel classification approach leveraging data from Reddit communities associated with the alt-right movement, we observe no persistent increase in hate speech or white nationalist language either over the course of the campaign or in the six months following Trump's election. While key campaign events and policy announcements produced brief spikes in hateful language, these bursts quickly dissipated. Overall we find no empirical support for the proposition that Trump's divisive campaign or election increased hate speech on Twitter.

    Date Posted

    Jan 11, 2021

  • Data Report
  • Data Report

    Influential Users in the Common Core and Black Lives Matter Social Media Conversation

    Data Report, NYU's Center for Social Media and Politics, 2020

    View Report View abstract

    This Data Report aims to map the pathways leading to issue politicization through identifying influential users within politically contentious topics on Twitter, using the online discussion over the Common Core State Standards (CCSS) and the Black Lives Matter (BLM) movement. We find that politically motivated popular users are the most influential users in both CCSS and BLM online conversations.

    Date Posted

    Dec 16, 2020

  • Working Paper

    News Sharing on Social Media: Mapping the Ideology of News Media Content, Citizens, and Politicians

    Working Paper, November 2020

    View Article View abstract

    This article examines the news sharing behavior of politicians and ordinary users by mapping the ideological sharing space of political information on social media. As data, we use the near-universal currency of online political information exchange: URLs (i.e. web links). We introduce a methodological approach (and statistical software) that unifies the measurement of political ideology online, using social media sharing data to jointly estimate the ideology of: (1) politicians; (2) social media users, and (3) the news sources that they share online. Second, we validate the measure by comparing it to well-known measures of roll call voting behavior for members of congress. Third, we show empirically that legislators who represent less competitive districts are more likely to share politically polarizing news than legislators with similar voting records in more competitive districts. Finally, we demonstrate that it is nevertheless not politicians, but ordinary users who share the most ideologically extreme content and contribute most to the polarized online news-sharing ecosystem. Our approach opens up many avenues for research into the communication strategies of elites, citizens, and other actors who seek to influence political behavior and sway public opinion by sharing political information online.

  • Data Report

    Online Issue Politicization: How the Common Core and Black Lives Matter Discussions Evolved on Social Media

    Data Report, NYU's Center for Social Media and Politics, 2020

    View Report View abstract

    Social media present an increasingly common path to issue politicization, as the distance between policy advocates and the masses is greatly reduced. In this Data Report, we analyze the discussions on Twitter of two issues (Black Lives Matter and Common Core State Standards) as they evolved over time. We show that politicization of the issues did not take the same path, and that different types of messages and senders were influential in expanding and shaping the discussions about the respective issues. For both issues, tweets by highly followed and verified users were widely shared, and contributed to a large downstream growth in the discussion. However, the substance of tweets mattered as well, with the use of angry language strongly correlated with measures of influence, alongside the important roles played by the use of hashtags. Finally, we find evidence that in the discussion around Common Core, some topics were far more important, including broaching issues of individual freedoms and personal values.

    Date Posted

    Sep 04, 2020

  • Book
  • Data Report
  • Journal Article

    Don’t Republicans Tweet Too? Using Twitter to Assess the Consequences of Political Endorsements by Celebrities

    Perspectives on Politics, 2020

    View Article View abstract

    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.


    Date Posted

    Sep 06, 2019

  • Journal Article

    Who Leads? Who Follows? Measuring Issue Attention and Agenda Setting by Legislators and the Mass Public Using Social Media Data

    American Political Science Review, 2019

    View Article View abstract

    Are legislators responsive to the priorities of the public? Research demonstrates a strong correspondence between the issues about which the public cares and the issues addressed by politicians, but conclusive evidence about who leads whom in setting the political agenda has yet to be uncovered. We answer this question with fine-grained temporal analyses of Twitter messages by legislators and the public during the 113th U.S. Congress. After employing an unsupervised method that classifies tweets sent by legislators and citizens into topics, we use vector autoregression models to explore whose priorities more strongly predict the relationship between citizens and politicians. We find that legislators are more likely to follow, than to lead, discussion of public issues, results that hold even after controlling for the agenda-setting effects of the media. We also find, however, that legislators are more likely to be responsive to their supporters than to the general public.

    Date Posted

    Jul 12, 2019

  • Journal Article

    Social Networks and Protest Participation: Evidence from 130 Million Twitter Users

    American Journal of Political Science, 2019

    View Article View abstract

    Pinning down the role of social ties in the decision to protest has been notoriously elusive largely due to data limitations. Social media and their global use by protesters offer an unprecedented opportunity to observe real-time social ties and online behavior, though often without an attendant measure of real-world behavior. We collect data on Twitter activity during the 2015 Charlie Hebdo protest in Paris, which, unusually, record real-world protest attendance and network structure measured beyond egocentric networks. We devise a test of social theories of protest that hold that participation depends on exposure to others' intentions and network position determines exposure. Our findings are strongly consistent with these theories, showing that protesters are significantly more connected to one another via direct, indirect, triadic, and reciprocated ties than comparable nonprotesters. These results offer the first large-scale empirical support for the claim that social network structure has consequences for protest participation.

    Date Posted

    Jul 01, 2019

    Tags

  • Journal Article

    Digital Dissent: An Analysis of the Motivational Contents of Tweets From an Occupy Wall Street Demonstration

    Motivation Science, 2019

    View Article View abstract

    Social scientific models of protest activity emphasize instrumental motives associated with rational self-interest and beliefs about group efficacy and symbolic motives associated with social identification and anger at perceived injustice. Ideological processes are typically neglected, despite the fact that protest movements occur in a sociopolitical context in which some people are motivated to maintain the status quo, whereas others are motivated to challenge it. To investigate the role of ideology and other social psychological processes in protest participation, we used manual and machine-learning methods to analyze the contents of 23,810 tweets sent on the day of the May Day 2012 Occupy Wall Street demonstration along with an additional 664,937 tweets (sent by 8,244 unique users) during the 2-week lead-up to the demonstration. Results revealed that social identification and liberal ideology were significant independent predictors of protest participation. The effect of social identification was mediated by the expression of collective efficacy, justice concerns, ideological themes, and positive emotion. The effect of liberalism was mediated by the expression of ideological themes, but conservatives were more likely to express ideological backlash against Occupy Wall Street than liberals were to express ideological support for the movement or demonstration. The expression of self-interest and anger was either negatively related or unrelated to protest participation. This work illustrates the promise (and challenge) of using automated methods to analyze new, ecologically valid data sources for studying protest activity and its motivational underpinnings — thereby informing strategic campaigns that employ collective action tactics. 

    Date Posted

    Feb 27, 2019

  • Journal Article

    Elites Tweet to Get Feet Off the Streets: Measuring Regime Social Media Strategies During Protest

    Political Science Research and Methods, 2019

    View Article View abstract

    As non-democratic regimes have adapted to the proliferation of social media, they have begun actively engaging with Twitter to enhance regime resilience. Using data taken from the Twitter accounts of Venezuelan legislators during the 2014 anti-Maduro protests in Venezuela, we fit a topic model on the text of the tweets and analyze patterns in hashtag use by the two coalitions. We argue that the regime’s best strategy in the face of an existential threat like the narrative developed by La Salida and promoted on Twitter was to advance many competing narratives that addressed issues unrelated to the opposition’s criticism. Our results show that the two coalitions pursued different rhetorical strategies in keeping with our predictions about managing the conflict advanced by the protesters. This article extends the literature on social media use during protests by focusing on active engagement with social media on the part of the regime. This approach corroborates and expands on recent research on inferring regime strategies from propaganda and censorship.

    Date Posted

    Mar 21, 2018

    Tags

  • Journal Article

    How Social Media Facilitates Political Protest: Information, Motivation, and Social Networks

    Advances in Political Psychology, 2018

    View Article View abstract

    It is often claimed that social media platforms such as Facebook and Twitter are profoundly shaping political participation, especially when it comes to protest behavior. Whether or not this is the case, the analysis of “Big Data” generated by social media usage offers unprecedented opportunities to observe complex, dynamic effects associated with large-scale collective action and social movements. In this article, we summarize evidence from studies of protest movements in the United States, Spain, Turkey, and Ukraine demonstrating that: (1) Social media platforms facilitate the exchange of information that is vital to the coordination of protest activities, such as news about transportation, turnout, police presence, violence, medical services, and legal support; (2) in addition, social media platforms facilitate the exchange of emotional and motivational contents in support of and opposition to protest activity, including messages emphasizing anger, social identification, group efficacy, and concerns about fairness, justice, and deprivation as well as explicitly ideological themes; and (3) structural characteristics of online social networks, which may differ as a function of political ideology, have important implications for information exposure and the success or failure of organizational efforts. Next, we issue a brief call for future research on a topic that is understudied but fundamental to appreciating the role of social media in facilitating political participation, namely friendship. In closing, we liken the situation confronted by researchers who are harvesting vast quantities of social media data to that of systems biologists in the early days of genome sequencing.

    Date Posted

    Feb 13, 2018

  • Book

    Twitter Wars: Sunni-Shia Conflict and Cooperation in the Digital Age

    Beyond Sunni and Shia: The Roots of Sectarianism in a Changing Middle East, 2018

    View Book

    Date Posted

    Feb 01, 2018

  • Journal Article

    Moral Discourse in the Twitterverse: Effects of Ideology and Political Sophistication on Language Use Among U.S. Citizens and Members of Congress

    Journal of Language and Politics, 2018

    View Article View abstract

    We analyzed Twitter language to explore hypotheses derived from moral foundations theory, which suggests that liberals and conservatives prioritize different values. In Study 1, we captured 11 million tweets from nearly 25,000 U.S. residents and observed that liberals expressed fairness concerns more often than conservatives, whereas conservatives were more likely to express concerns about group loyalty, authority, and purity. Increasing political sophistication exacerbated ideological differences in authority and group loyalty. At low levels of sophistication, liberals used more harm language, but at high levels of sophistication conservatives referenced harm more often. In Study 2, we analyzed 59,000 tweets from 388 members of the U.S. Congress. Liberal legislators used more fairness- and harm-related words, whereas conservative legislators used more authority-related words. Unexpectedly, liberal legislators used more language pertaining to group loyalty and purity. Follow-up analyses suggest that liberals and conservatives in Congress use similar words to emphasize different policy priorities.

  • Journal Article

    The Islamic State’s Information Warfare: Measuring the Success of ISIS’s Online Strategy

    Journal of Language and Politics, 2018

    View Article View abstract

    How successful is the Islamic State’s online strategy? To what extent does the organization achieve its goals of attracting a global audience, broadcasting its military successes, and marketing the Caliphate? Using Twitter and YouTube search data, we assess how suspected ISIS accounts, sympathizers, and opponents behave across two social media platforms, offering key insights into the successes and limitations of ISIS’ information warfare strategy. Analyzing the tweet content and metadata from 16,364 suspected ISIS accounts, we find that a core network of ISIS Twitter users are producing linguistically diverse narratives, touting battlefield victories and depicting utopian life in the Caliphate. Furthermore, a dataset of over 70 million tweets, as well as analysis of YouTube search data, indicates that although pro-ISIS content spreads globally and remains on message, it is far less prolific than anti-ISIS content. However, this anti-ISIS content is not necessarily anti-extremist or aligned with Western policy goals.

    Date Posted

    Oct 18, 2017

    Tags

  • Journal Article

    From Liberation to Turmoil: Social Media and Democracy

    The Journal of Democracy, 2017

    View Article View abstract

    How can one technology—social media—simultaneously give rise to hopes for liberation in authoritarian regimes, be used for repression by these same regimes, and be harnessed by antisystem actors in democracy? We present a simple framework for reconciling these contradictory developments based on two propositions: 1) that social media give voice to those previously excluded from political discussion by traditional media, and 2) that although social media democratize access to information, the platforms themselves are neither inherently democratic nor nondemocratic, but represent a tool political actors can use for a variety of goals, including, paradoxically, illiberal goals.

    Date Posted

    Oct 07, 2017

  • Journal Article

    Social Media and EuroMaidan: A Review Essay

    Slavic Review, 2017

    View Article View abstract

    As more than a billion people had done previously, on November 21, 2013, Ukrainian journalist and activist Mustafa Nayem wrote a Facebook post; this post, however, would have a much larger impact on subsequent political developments than most that had preceded it. Frustrated with President Viktor Yanukovych’s decision not to sign a long-promised association agreement with the European Union, Nayem asked others who shared his frustration to comment on his post. Even more importantly, Nayem wrote that if the post received at least 1,000 comments from people willing to join him, they should all go to Independence Square to protest. And indeed they did: starting with just a few thousand people, the protests would swell to be the largest since Ukraine’s independence, particularly after police used force against protesters at the end of November 2013. Eventually, these protests led to the resignation of the government, the exile of the former president, and indirectly to the secession of Crimea and the ongoing conflict in the eastern part of the country.

    Date Posted

    May 02, 2017

    Tags

  • Journal Article

    Liberal and Conservative Values: What We Can Learn from Congressional Tweets

    Political Psychology, 2018

    View Article View abstract

    Past research using self-report questionnaires administered to ordinary citizens demonstrates that value priorities differ as a function of one's political ideology, but it is unclear whether this conclusion applies to political elites, who are presumably seeking to appeal to very broad constituencies. We used quantitative methods of textual analysis to investigate value-laden language in a collection of 577,555 messages sent from the public Twitter accounts of over 400 members of the U.S. Congress between 2012 and 2014. Consistent with theoretical expectations, we observed that Republican and conservative legislators stressed values of tradition, conformity, and national security (as well as self-direction), whereas Democratic and liberal legislators stressed values of benevolence, universalism, hedonism, and social/economic security (as well as achievement). Implications for the large-scale observational study of political psychology are explored.

    Date Posted

    Mar 29, 2017

  • Journal Article

    Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment

    Political Behavior, 2017

    View Article View abstract

    I conduct an experiment which examines the impact of group norm promotion and social sanctioning on racist online harassment. Racist online harassment de-mobilizes the minorities it targets, and the open, unopposed expression of racism in a public forum can legitimize racist viewpoints and prime ethnocentrism. I employ an intervention designed to reduce the use of anti-black racist slurs by white men on Twitter. I collect a sample of Twitter users who have harassed other users and use accounts I control (“bots”) to sanction the harassers. By varying the identity of the bots between in-group (white man) and out-group (black man) and by varying the number of Twitter followers each bot has, I find that subjects who were sanctioned by a high-follower white male significantly reduced their use of a racist slur. This paper extends findings from lab experiments to a naturalistic setting using an objective, behavioral outcome measure and a continuous 2-month data collection period. This represents an advance in the study of prejudiced behavior.

    Date Posted

    Nov 11, 2016

  • Book

    Date Posted

    Mar 05, 2016

    Tags

  • 1
  • 2