Most people receive political news from social media platforms. Unlike traditional media, these platforms algorithmically determine the order in which news is presented, in part relying on an article’s popularity (i.e. number of likes, shares, and comments) to determine its ranking. To what extent does sorting the news by popularity influence people’s attitudes toward politics? With two large, nationally representative samples of adults and a novel experimental design, we find that ranking news articles by their popularity has consequential effects that vary depending on the partisan composition of the group upon which the rankings are based. Overall, algorithmic sorting exacerbates the tendency to “like” news that conform to the dominant viewpoint of the reference group. For example, when the group is ideologically like-minded, the in-party bias in “liking” creates a self-perpetuating cycle, where attitudinally congruent articles remain at the top of the feed. When the reference group is rather composed of out-party members, politically incongruent items rise to the top. While this helps to expose readers to new information, they also become disengaged from reading and sharing political news. Overall, our study holds important implications for how using social media as an outlet for political information can influence–and even polarize–our political preferences.
- online experiments
- political news
- social media
ASJC Scopus subject areas
- Sociology and Political Science