The effects of Facebook and Instagram on the 2020 election: A deactivation experiment.

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.

The shared psychological roots of prejudice and conspiracy theory belief.

The psychological literature on prejudice and conspiracy theory belief have generally remained distinct, implicitly treating the two as unrelated phenomena. In this brief review, I demonstrate that the two phenomena share at least three dispositional precursors: ingroup bias, right-wing ideology (specifically right-wing authoritarianism and social dominance orientation), and need for closure. The evidence I present suggests that prejudice and conspiracy beliefs may be more closely related both conceptually and normatively than existing research has indicated. In particular, they may appear in the same individuals, cause similar kinds of harms in adherents as well as target populations, and respond to similar counteractive interventions.

TikToks Lead to Higher Knowledge and Perceived Severity of Sexual Violence among Adolescent Men.

Social media communication is a promising way to deliver important health messages about sexual violence to a key population of adolescent men. The researchers conducted an online, between-participants experiment to examine the impact of personal narrative TikToks about sexual violence on adolescent men. Participants were adolescent men (n = 580) aged 15 to 19 (M = 17.3, SD = 1.43). Participants were randomly assigned to treatment (personal narrative TikToks about sexual violence) or control (hair braiding TikTok tutorials) conditions. Adolescent men who viewed personal narrative TikToks about sexual violence had higher knowledge of consequences and higher perceived severity of sexual violence. Additionally, adolescent men found personal narrative TikToks more attention-grabbing (vs. control) and did not have negative reactions. Findings that short (approximately one-minute) TikTok videos led to differences in knowledge and beliefs among, and were interesting and not aversive to, adolescent men are important for sexual violence prevention research. Health messages on TikTok can help shift adolescent perceptions of sexual violence, which is a key starting point towards changing norms.

Like-minded sources on Facebook are prevalent but not polarizing.

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.

How do social media feed algorithms affect attitudes and behavior in an election campaign?

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.

Asymmetric ideological segregation in exposure to political news on Facebook.

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.

Reshares on social media amplify political news but do not detectably affect beliefs or opinions.

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.

A Self-management SMS Text Messaging Intervention for People With Inflammatory Bowel Disease: Feasibility and Acceptability Study.

BACKGROUND: Mobile health technologies can be useful for providing disease self-management information and support to people with inflammatory bowel disease (IBD). OBJECTIVE: The aim of this study was to test a self-management SMS text messaging intervention for people with IBD. Our goal was to examine intervention feasibility, acceptability, and engagement and to preliminarily evaluate improvements in certain self-reported health outcomes among participants. METHODS: We developed an SMS text messaging program called Text4IBD. The program sent daily support messages and resources about disease self-management over the course of a 2-week, single-group, pretest-posttest intervention to participants (N=114) diagnosed with IBD. We examined intervention feasibility, acceptability, and engagement through Text4IBD message topic recall and use of resources (ie, visiting supplemental websites recommended by the Text4IBD program). We also assessed pretest-posttest measures of IBD-related distress, self-efficacy, perceived support, use of coping strategies, and medication adherence. Analyses examined participants' evaluations of the intervention and compared pretest-posttest changes in secondary outcomes using paired-samples statistics. RESULTS: Approximately all participants who completed the intervention (n=105) were receptive to Text4IBD and viewed the program as feasible and acceptable. In addition, most participants (103/105, 98.1%) recalled at least one of the message topics sent by the program, and 79% (83/105) of them self-reported engaging with at least one of the external self-management resources recommended by the Text4IBD program. Pretest-posttest results showed reduced IBD-related distress (mean 3.33, SD 0.68 vs mean 2.86, SD 0.73; P<.001) and improvements in most other secondary outcomes. CONCLUSIONS: Findings from this study highlight the value of SMS text messaging as a useful digital medium for providing support to people with IBD, particularly to those who may struggle with disease-related distress. Text4IBD was highly feasible and acceptable and may help people self-manage their IBD. Future studies should aim to evaluate this program in a randomized controlled trial in clinical settings.

The advantage of the right in social media news sharing.

We analyze social media activity during one of the largest protest mobilizations in US history to examine ideological asymmetries in the posting of news content. Using an unprecedented combination of four datasets (tracking offline protests, social media activity, web browsing, and the reliability of news sources), we show that there is no evidence of unreliable sources having any prominent visibility during the protest period, but we do identify asymmetries in the ideological slant of the sources shared on social media, with a clear bias towards right-leaning domains. These results support the "amplification of the right" thesis, which points to the structural conditions (social and technological) that lead to higher visibility of content with a partisan bent towards the right. Our findings provide evidence that right-leaning sources gain more visibility on social media and reveal that ideological asymmetries manifest themselves even in the context of movements with progressive goals.

Meaningful measures of human society in the twenty-first century.

Science rarely proceeds beyond what scientists can observe and measure, and sometimes what can be observed proceeds far ahead of scientific understanding. The twenty-first century offers such a moment in the study of human societies. A vastly larger share of behaviours is observed today than would have been imaginable at the close of the twentieth century. Our interpersonal communication, our movements and many of our everyday actions, are all potentially accessible for scientific research; sometimes through purposive instrumentation for scientific objectives (for example, satellite imagery), but far more often these objectives are, literally, an afterthought (for example, Twitter data streams). Here we evaluate the potential of this massive instrumentation-the creation of techniques for the structured representation and quantification-of human behaviour through the lens of scientific measurement and its principles. In particular, we focus on the question of how we extract scientific meaning from data that often were not created for such purposes. These data present conceptual, computational and ethical challenges that require a rejuvenation of our scientific theories to keep up with the rapidly changing social realities and our capacities to capture them. We require, in other words, new approaches to manage, use and analyse data.

False equivalencies: Online activism from left to right.

Digital media are critical for contemporary activism-even low-effort "clicktivism" is politically consequential and contributes to offline participation. We argue that in the United States and throughout the industrialized West, left- and right-wing activists use digital and legacy media differently to achieve political goals. Although left-wing actors operate primarily through "hashtag activism" and offline protest, right-wing activists manipulate legacy media, migrate to alternative platforms, and work strategically with partisan media to spread their messages. Although scholarship suggests that the right has embraced strategic disinformation and conspiracy theories more than the left, more research is needed to reveal the magnitude and character of left-wing disinformation. Such ideological asymmetries between left- and right-wing activism hold critical implications for democratic practice, social media governance, and the interdisciplinary study of digital politics.

Assessing the Russian Internet Research Agency's impact on the political attitudes and behaviors of American Twitter users in late 2017.

There is widespread concern that Russia and other countries have launched social-media campaigns designed to increase political divisions in the United States. Though a growing number of studies analyze the strategy of such campaigns, it is not yet known how these efforts shaped the political attitudes and behaviors of Americans. We study this question using longitudinal data that describe the attitudes and online behaviors of 1,239 Republican and Democratic Twitter users from late 2017 merged with nonpublic data about the Russian Internet Research Agency (IRA) from Twitter. Using Bayesian regression tree models, we find no evidence that interaction with IRA accounts substantially impacted 6 distinctive measures of political attitudes and behaviors over a 1-mo period. We also find that interaction with IRA accounts were most common among respondents with strong ideological homophily within their Twitter network, high interest in politics, and high frequency of Twitter usage. Together, these findings suggest that Russian trolls might have failed to sow discord because they mostly interacted with those who were already highly polarized. We conclude by discussing several important limitations of our study-especially our inability to determine whether IRA accounts influenced the 2016 presidential election-as well as its implications for future research on social media influence campaigns, political polarization, and computational social science.