Divergent patterns of engagement with partisan and low-quality news across seven social media platforms

Journal article

In recent years, social media has become increasingly fragmented, as platforms evolve and new alternatives emerge. Yet most research studies a single platform—typically X/Twitter, or occasionally Facebook—leaving little known about the broader social media landscape. Here, we shed light on patterns of cross-platform variation in the high-stakes context of news sharing. We examine the relationship between user engagement and news domains’ political orientation and quality across seven platforms: X/Twitter, BlueSky, TruthSocial, Gab, GETTR, Mastodon, and LinkedIn. Using an exhaustive sample, we analyze all (over 10 million) posts containing links to news domains shared on these platforms during January 2024. We find that news shared on platforms with more conservative user bases is significantly lower quality on average. Turning to engagement, we find—contrary to hypotheses of a consistent “right-wing advantage” on social media—that the relationship between political lean and engagement is strongly heterogeneous across platforms. Conservative news posts receive more engagement on platforms where most content is conservative, and vice versa for liberal news posts, consistent with an “echo platform” perspective. In contrast, the relationship between news quality and engagement is strikingly consistent: Across all platforms examined, a given user’s lower-quality news posts received higher average engagement, even though higher-quality news is substantially more prevalent and garners far more total engagement across posts. This pattern holds when accounting for poster-level variation and is observed even in the absence of ranking algorithms, suggesting that user preferences—not algorithmic bias—may underlie the underperformance of higher-quality news.

Authors: Mosleh, M; Allen, J; Rand, DG

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: National Academy of Sciences
• Journal: Proceedings of the National Academy of Sciences
• Volume: 122
• Issue: 44
• Article number: e2425739122
• Publication date: 2025-10-30
• Acceptance date: 2025-08-27
• DOI: 10.1073/pnas.2425739122
• EISSN: 1091-6490
• ISSN: 0027-8424
• Language: English
• Keywords: social media; political lean; misinformation