Data and Code for: Social Media, News Consumption, and Polarization: Evidence from a Field Experiment

Does the consumption of ideologically congruent news on social media exacerbate polarization? I estimate the effects of social media news exposure by conducting a large field experiment randomly offering participants subscriptions to conservative or liberal news outlets on Facebook. I collect data on the causal chain of media effects: subscriptions to outlets, exposure to news on Facebook, visits to online news sites, and sharing of posts, as well as changes in political opinions and attitudes. Four main findings emerge. First, random variation in exposure to news on social media substantially affects the slant of news sites individuals visit. Second, exposure to counter-attitudinal news decreases negative attitudes toward the opposing political party. Third, in contrast to the effect on attitudes, I find no evidence that the political leanings of news outlets affect political opinions. Fourth, Facebook's algorithm is less likely to supply individuals with posts from counter-attitudinal outlets, conditional on individuals subscribing to them. Together, the results suggest that social media algorithms may limit exposure to counter-attitudinal news and thus increase polarization.<br>

社交媒体平台上接触意识形态契合的新闻是否会加剧政治极化？本研究通过开展大规模田野实验，随机向参与者提供Facebook平台上保守派或自由派新闻媒体的订阅权限，以此估算社交媒体新闻接触产生的影响。本研究收集了媒体影响因果链相关数据：涵盖新闻媒体订阅情况、Facebook平台内的新闻接触量、在线新闻网站访问量、帖子分享行为，以及政治观点与态度的变化。本研究得出四项核心发现：其一，社交媒体平台内新闻接触的随机变化，会显著影响个体访问的新闻网站的政治立场偏向；其二，接触与自身立场相悖的新闻，会降低个体对对立政党的负面态度；其三，与态度层面的影响效果不同，本研究未发现新闻媒体的政治倾向会对个体政治观点产生影响的证据；其四，在个体已订阅对立立场新闻媒体的前提下，Facebook算法向其推送该类媒体帖子的概率更低。综合来看，研究结果表明社交媒体算法可能会限制个体接触与自身立场相悖的新闻，进而加剧政治极化。