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#human-computer interaction Preprint Open access

Ideological discrepancy between Facebook pages and shared news is associated with reaction homogeneity

Thiago Magrin Jordan Kobellarz Pedro O. S. Vaz-de-Melo Thiago H. Silva
Oct 2026
Human-computer Interaction

Abstract

Cross-cutting political content is often expected to mitigate polarization, yet encounters across ideological lines do not necessarily foster more constructive engagement. We analyzed 4,584 posts from 1,243 Facebook pages sharing 761 political news links in a dataset centered on Brazil's 2018 presidential election, and introduced Bias Discrepancy, which measures how far a shared link lies from the page's ideological sharing repertoire. We examined how Bias Discrepancy related to Content Reaction Positivity (how positively the same link was received in other posts), the Reaction Homogeneity Index (whether a post's own reactions were one-sided or mixed), and the toxicity of the page's accompanying text. Reaction homogeneity was lowest at both extremes of Bias Discrepancy, and posts furthest from the page's repertoire had the highest average toxicity. In a multivariable model, greater Bias Discrepancy was associated with lower reaction homogeneity, with a magnitude similar to the link's content bias and toxicity and smaller than Content Reaction Positivity. When a page shared news that departed from its repertoire, its accompanying text tended to be more toxic and its audience's reactions more mixed.

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