Academic Research

Social media is used by millions of Americans to acquire political news and information. Most of this research has focused on understanding the way social media consumption affects the political behavior and preferences of White Americans. Much less is known about Latinos’ political activity on social media, who are not only the largest racial/ethnic minority group in the U.S., but they also continue to exhibit diverse political preferences. Moreover, about 30% of Latinos rely primarily on Spanish-language news sources (Spanish-dominant Latinos) and another 30% are bilingual. Given that Spanish-language social media is not as heavily monitored for misinformation than its English-language counterparts (Valencia, 2021; Paul, 2021), Spanish-dominant Latinos who rely on social media for news may be more susceptible to political misinformation than those Latinos who are exposed to English-language social media. We address this contention by fielding an original study that sampled a large number of Latino and White respondents. Consistent with our expectations, Latinos who rely on Spanish-language social media are more likely to believe in election fraud than those who use both English and Spanish social media new sources. We also find that Latinos engage in more political activities on social media when compared to White Americans, particularly on their social media of choice, WhatsApp.

Skepticism about the outcome of the 2020 presidential election in the United States led to a historic attack on the Capitol on January 6th, 2021 and represents one of the greatest challenges to America's democratic institutions in over a century. Narratives of fraud and conspiracy theories proliferated over the fall of 2020, finding fertile ground across online social networks, although little is know about the extent and drivers of this spread. In this article, we show that users who were more skeptical of the election's legitimacy were more likely to be recommended content that featured narratives about the legitimacy of the election. Our findings underscore the tension between an "effective" recommendation system that provides users with the content they want, and a dangerous mechanism by which misinformation, disinformation, and conspiracies can find their way to those most likely to believe them.

To mitigate the spread of false news, researchers need to understand who visits low-quality news sites, what brings people to those sites, and what content they prefer to consume. Due to challenges in observing most direct website traffic, existing research primarily relies on alternative data sources, such as engagement signals from social media posts. However, such signals are at best only proxies for actual website visits. During an audit of far-right news websites, we discovered that The Gateway Pundit (TGP) has made its web traffic data publicly available, giving us a rare opportunity to understand what news pages people actually visit. We collected 68 million web traffic visits to the site over a one-month period and analyzed how people consume news via multiple features. Our referral analysis shows that search engines and social media platforms are the main drivers of traffic; our geo-location analysis reveals that TGP is more popular in counties where more people voted for Trump in 2020. In terms of content, topics related to 2020 US presidential election and 2021 US capital riot have the highest average number of visits. We also use these data to quantify to what degree social media engagement signals correlate with actual web visit counts. To do so, we collect Facebook and Twitter posts with URLs from TGP during the same time period. We show that all engagement signals positively correlate with web visit counts, but with varying correlation strengths. For example, total interaction on Facebook correlates better than Twitter retweet count. Our insights can also help researchers choose the right metrics when they measure the impact of news URLs on social media.

To what extent does the YouTube recommendation algorithm push users into echo chambers, ideologically biased content, or rabbit holes? Despite growing popular concern, recent work suggests that the recommendation algorithm is not pushing users into these echo chambers. However, existing research relies heavily on the use of anonymous data collection that does not account for the personalized nature of the recommendation algorithm. We asked a sample of real users to install a browser extension that downloaded the list of videos they were recommended. We instructed these users to start on an assigned video and then click through 20 sets of recommendations, capturing what they were being shown in real time as they used the platform logged into their real accounts. Using a novel method to estimate the ideology of a YouTube video, we demonstrate that the YouTube recommendation algorithm does, in fact, push real users into mild ideological echo chambers where, by the end of the data collection task, liberals and conservatives received different distributions of recommendations from each other, though this difference is small. While we find evidence that this difference increases the longer the user followed the recommendation algorithm, we do not find evidence that many go down `rabbit holes' that lead them to ideologically extreme content. Finally, we find that YouTube pushes all users, regardless of ideology, towards moderately conservative and an increasingly narrow range of ideological content the longer they follow YouTube's recommendations.

As the primary arena for viral misinformation shifts toward transnational threats, the search continues for scalable countermeasures compatible with principles of transparency and free expression. We conducted a randomized field experiment evaluating the impact of source credibility labels embedded in users’ social feeds and search results pages. By combining representative surveys (n = 3337) and digital trace data (n = 968) from a subset of respondents, we provide a rare ecologically valid test of such an intervention on both attitudes and behavior. On average across the sample, we are unable to detect changes in real-world consumption of news from low-quality sources after 3 weeks. We can also rule out small effects on perceived accuracy of popular misinformation spread about the Black Lives Matter movement and coronavirus disease 2019. However, we present suggestive evidence of a substantively meaningful increase in news diet quality among the heaviest consumers of misinformation. We discuss the implications of our findings for scholars and practitioners.

In this study, we analyze for the first time newly available engagement data covering millions of web links shared on Facebook to describe how and by which categories of U.S. users different types of news are seen and shared on the platform. We focus on articles from low-credibility news publishers, credible news sources, purveyors of clickbait, and news specifically about politics, which we identify through a combination of curated lists and supervised classifiers. Our results support recent findings that more fake news is shared by older users and conservatives and that both viewing and sharing patterns suggest a preference for ideologically congenial misinformation. We also find that fake news articles related to politics are more popular among older Americans than other types, while the youngest users share relatively more articles with clickbait headlines. Across the platform, however, articles from credible news sources are shared over 5.5 times more often and viewed over 7.5 times more often than articles from low-credibility sources. These findings offer important context for researchers studying the spread and consumption of information — including misinformation — on social media.

This paper uses geolocated Twitter histories from approximately 25,000 individuals in 6 different time zones and 3 different countries to construct a proper time-zone dependent hourly baseline for social media activity studies.  We establish that, across multiple regions and time periods, interaction with social media is strongly conditioned by traditional bio-rhythmic or “Circadian” patterns, and that in the United States, this pattern is itself further conditioned by the ideological bent of the user. Using a time series of these histories around the 2016 U.S. Presidential election, we show that external events of great significance can disrupt traditional social media activity patterns, and that this disruption can be significant (in some cases doubling the amplitude and shifting the phase of activity up to an hour). We find that the disruption of use patterns can last an extended period of time, and in many cases, aspects of this disruption would not be detected without a circadian baseline.

In January 2019, YouTube announced it would exclude potentially harmful content from video recommendations but allow such videos to remain on the platform. While this step intends to reduce YouTube's role in propagating such content, continued availability of these videos in other online spaces makes it unclear whether this compromise actually reduces their spread. To assess this impact, we apply interrupted time series models to measure whether different types of YouTube sharing in Twitter and Reddit changed significantly in the eight months around YouTube's announcement. We evaluate video sharing across three curated sets of potentially harmful, anti-social content: a set of conspiracy videos that have been shown to experience reduced recommendations in YouTube, a larger set of videos posted by conspiracy-oriented channels, and a set of videos posted by alternative influence network (AIN) channels. As a control, we also evaluate effects on video sharing in a dataset of videos from mainstream news channels. Results show conspiracy-labeled and AIN videos that have evidence of YouTube's de-recommendation experience a significant decreasing trend in sharing on both Twitter and Reddit. For videos from conspiracy-oriented channels, however, we see no significant effect in Twitter but find a significant increase in the level of conspiracy-channel sharing in Reddit. For mainstream news sharing, we actually see an increase in trend on both platforms, suggesting YouTube's suppressing particular content types has a targeted effect. This work finds evidence that reducing exposure to anti-social videos within YouTube, without deletion, has potential pro-social, cross-platform effects. At the same time, increases in the level of conspiracy-channel sharing raise concerns about content producers' responses to these changes, and platform transparency is needed to evaluate these effects further.

“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.

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.

The role of the media in influencing people’s attitudes and opinions is difficult to demonstrate because media consumption by survey respondents is usually unobserved in datasets containing information on attitudes and vote choice. This paper leverages behavioral data combined with responses from a multi-wave panel to test whether Democrats who see more stories from liberal news sources on Twitter develop more liberal positions over time and, conversely, whether Republicans are more likely to revise their views in a conservative direction if they are exposed to more news on Twitter from conservative media sources. We find evidence that exposure to ideologically framed information and arguments changes voters’ own positions, but has a limited impact on perceptions of where the candidates stand on the issues.

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.

“Clickbait” headlines designed to entice people to click are frequently used by both legitimate and less-than-legitimate news sources. Contemporary clickbait headlines tend to use emotional partisan appeals, raising concerns about their impact on consumers of online news. This article reports the results of a pair of experiments with different sets of subject pools: one conducted using Facebook ads that explicitly target people with a high preference for clickbait, the other using a sample recruited from Amazon’s Mechanical Turk. We estimate subjects’ individual-level preference for clickbait, and randomly assign sets of subjects to read either clickbait or traditional headlines. Findings show that older people and non-Democrats have a higher “preference for clickbait,” but reading clickbait headlines does not drive affective polarization, information retention, or trust in media.

A major point of debate in the study of the Internet and politics is the extent to which social media platforms encourage citizens to inhabit online “bubbles” or “echo chambers,” exposed primarily to ideologically congenial political information. To investigate this question, we link a representative survey of Americans with data from respondents’ public Twitter accounts (N = 1,496). We then quantify the ideological distributions of users’ online political and media environments by merging validated estimates of user ideology with the full set of accounts followed by our survey respondents (N = 642,345) and the available tweets posted by those accounts (N ~ 1.2 billion). We study the extent to which liberals and conservatives encounter counter-attitudinal messages in two distinct ways: (a) by the accounts they follow and (b) by the tweets they receive from those accounts, either directly or indirectly (via retweets). More than a third of respondents do not follow any media sources, but among those who do, we find a substantial amount of overlap (51%) in the ideological distributions of accounts followed by users on opposite ends of the political spectrum. At the same time, however, we find asymmetries in individuals’ willingness to venture into cross-cutting spaces, with conservatives more likely to follow media and political accounts classified as left-leaning than the reverse. Finally, we argue that such choices are likely tempered by online news watching behavior.

So-called “fake news” has renewed concerns about the prevalence and effects of misinformation in political campaigns. Given the potential for widespread dissemination of this material, we examine the individual-level characteristics associated with sharing false articles during the 2016 U.S. presidential campaign. To do so, we uniquely link an original survey with respondents’ sharing activity as recorded in Facebook profile data. First and foremost, we find that sharing this content was a relatively rare activity. Conservatives were more likely to share articles from fake news domains, which in 2016 were largely pro-Trump in orientation, than liberals or moderates. We also find a strong age effect, which persists after controlling for partisanship and ideology: On average, users over 65 shared nearly seven times as many articles from fake news domains as the youngest age group.

How accurate are survey-based measures of social media use, in particular about political topics? We answer this question by linking original survey data collected during the U.S. 2016 election campaign with respondents’ observed social media activity. We use supervised machine learning to classify whether these Twitter and Facebook account data are content related to politics. We then benchmark our survey measures on frequency of posting about politics and the number of political figures followed. We find that, on average, our self-reported survey measures tend to correlate with observed social media activity. At the same time, we also find a worrying amount of individual-level discrepancy and problems related to extreme outliers. Our recommendations are twofold. The first is for survey questions about social media use to provide respondents with options covering a wider range of activity, especially in the long tail. The second is for survey questions to include specific content and anchors defining what it means for a post to be “about politics.”

Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.

Scholars have debated whether social media platforms, by allowing users to select the information to which they are exposed, may lead people to isolate themselves from viewpoints with which they disagree, thereby serving as political “echo chambers.” We investigate hypotheses concerning the circumstances under which Twitter users who communicate about elections would engage with (a) supportive, (b) oppositional, and (c) mixed political networks. Based on online surveys of representative samples of Italian and German individuals who posted at least one Twitter message about elections in 2013, we find substantial differences in the extent to which social media facilitates exposure to similar versus dissimilar political views. Our results suggest that exposure to supportive, oppositional, or mixed political networks on social media can be explained by broader patterns of political conversation (i.e., structure of offline networks) and specific habits in the political use of social media (i.e., the intensity of political discussion). These findings suggest that disagreement persists on social media even when ideological homophily is the modal outcome, and that scholars should pay more attention to specific situational and dispositional factors when evaluating the implications of social media for political communication.

We estimated ideological preferences of 3.8 million Twitter users and, using a data set of nearly 150 million tweets concerning 12 political and nonpolitical issues, explored whether online communication resembles an “echo chamber” (as a result of selective exposure and ideological segregation) or a “national conversation.” We observed that information was exchanged primarily among individuals with similar ideological preferences in the case of political issues (e.g., 2012 presidential election, 2013 government shutdown) but not many other current events (e.g., 2013 Boston Marathon bombing, 2014 Super Bowl). Discussion of the Newtown shootings in 2012 reflected a dynamic process, beginning as a national conversation before transforming into a polarized exchange. With respect to both political and nonpolitical issues, liberals were more likely than conservatives to engage in cross-ideological dissemination; this is an important asymmetry with respect to the structure of communication that is consistent with psychological theory and research bearing on ideological differences in epistemic, existential, and relational motivation. Overall, we conclude that previous work may have overestimated the degree of ideological segregation in social-media usage.