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

TL;DR

This study finds that users consistently get more engagement for low-quality news posts across seven social media platforms, regardless of political lean.

Contribution

The study reveals a consistent pattern of higher engagement for low-quality news posts across platforms, challenging assumptions about algorithmic bias.

Findings

Lower-quality news posts receive more engagement than higher-quality ones across all platforms.

Conservative news gets more engagement on right-leaning platforms, and vice versa for liberal news.

The pattern of engagement holds even without algorithmic ranking, suggesting user preferences drive it.

Abstract

When analyzing over 10 million posts across 7 social media platforms, we find stark differences across platforms in the political lean and quality of news shared, as well as qualitatively different patterns of engagement. While lower-quality news domains are shared more on right-leaning platforms, and news from a platform’s dominant political orientation receives more engagement, we nonetheless find that a given user's lower-quality news posts consistently attract more user engagement than their higher-quality content—even on left-leaning platforms. This pattern holds even though we account for all user-level variation in engagement, and even on platforms without complex algorithms. These findings highlight the importance of examining cross-platform variation and offer insights into political echo chambers and the spread of misinformation.

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.

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