Partisan Selective Engagement: Evidence from Facebook

Amplifying Counter-Public Spheres on Social Media: News Sharing of Alternative Versus Traditional Media After the 2019 Chilean Uprising

“…The API tracks and quantifies performance indicators for every post by every tracked account, providing data on different types of user reactions (i.e., shares, views, comments, likes, and so forth). In this article, we analyze data on users’ engagement with Facebook posts (for a similar approach, see Garz et al, 2020; Vargo & Hopp, 2020). To be sure, engagement is not equivalent to exposure, though the two phenomena are related to each other (Bright, 2016).…”

Online Political Debates

“…The former investigates the extent to which partisan users share different posts on Facebook, finding evidence for asymmetric patterns across ideological lines. The latter focuses on how ideological homophily in Facebook friends' and Facebook's algorithm exacerbate partisan differences in exposure to news.3 This part of our findings is related toGarz, Sörensen, and Stone (2020). They analyze Facebook posts by German news sources covering the lifting of immunity for German politicians between 2012 on 2017 and find that posts that are congenial with the outlet's ideology receive more likes, shares, and comments.…”

Crowding Out the Truth? A Simple Model of Misinformation, Polarization and Meaningful Social Interactions

“…In words, we always assume that individuals highlight only if the news item reports a signal sufficiently close to their prior (Garz et al, 2020). Moreover, in the flat case the probability of highlighting a news item (p A ) is independent of the individual's signal x n (again, provided that the news item reports a signal sufficiently close to individual's prior).…”

“…In terms of clicking choices, we assume that with some positive probability individuals have some preference for choosing confirmatory news (Gentzkow and Shapiro, 2010;Yom-Tov et al, 2013;White and Horvitz, 2015;Flaxman et al, 2016) and, at the same time, also for news items that are higher ranked (Pan et al, 2007;Novarese and Wilson, 2013;Glick et al, 2014;Epstein and Robertson, 2015). In terms of highlights, we assume that with some probability individuals highlight a news item, provided it is sufficiently close to their prior beliefs (Garz et al, 2020) and the more so the more extreme their prior beliefs are (Bakshy et al, 2015;Grinberg et al, 2019;Pew, 2019;Hopp et al, 2020).…”