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The processing and evaluation of news content on social media is influenced by peer-user commentary

Social Work

The processing and evaluation of news content on social media is influenced by peer-user commentary

A. B. Boot, K. Dijkstra, et al.

Discover how Likes and peer-user comments shape our perceptions of online news in this intriguing study by Arnout B. Boot, Katinka Dijkstra, and Rolf A. Zwaan. The research uncovers the powerful influence of negative comments on reader attitudes, credibility, and share intent, highlighting the psychology behind our online interactions.

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~3 min • Beginner • English
Abstract
Contemporary news often spreads via social media. This study investigated whether the processing and evaluation of online news content can be influenced by Likes and peer-user comments. An online experiment was designed, using a custom-built website that resembled Facebook, to explore how Likes, positive comments, negative comments, or a combination of positive and negative comments would affect the reader's processing of news content. The results showed that especially negative comments affected the readers' personal opinions about the news content, even in combination with other positive comments: They (1) induced more negative attitudes, (2) lowered intent to share it, (3) reduced agreement with conveyed ideas, (4) lowered perceived attitude of the general public, and (5) decreased the credibility of the content. Against expectations, the presence of Likes did not affect the readers, irrespective of the news content. An important consideration is that, while the negative comments were persuasive, they comprised subjective, emotive, and fallacious rhetoric. Finally, negativity bias, the perception of expert authority, and cognitive heuristics are discussed as potential explanations for the persuasive effect of negative comments.
Publisher
Humanities & Social Sciences Communications
Published On
Sep 10, 2021
Authors
Arnout B. Boot, Katinka Dijkstra, Rolf A. Zwaan
Tags
online news
Likes
peer-user comments
negative comments
cognitive heuristics
negativity bias
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