Negative news posts are less prevalent and generate lower user engagement than non-negative news posts across six countries

2025-07-25

AI Summary

This study investigates the prevalence and user engagement with negative news on social media, specifically comparing the dissemination dynamics of political versus non-political negative content. Method: Leveraging a multilingual dataset of 6.08 million Facebook posts across six countries, we develop a dual-dimension classifier to annotate posts along political and valence (negative/neutral/positive) axes, and employ statistical modeling to analyze engagement metrics. Contribution/Results: We provide the first systematic, cross-national, multilingual empirical evidence on the proportion and interaction effects of negative news. Negative news constitutes only 12.6% of all news posts; it receives 15% fewer likes and 13% fewer comments than neutral or positive content, contributing merely 10.2%–13.1% of total user interactions. These findings challenge the widely held “negativity bias” hypothesis, demonstrating that negative news exhibits limited actual virality—offering a critical benchmark for understanding news ecosystems and user behavior in the digital age.

Technology Category

• Natural Language Processing: Fact-Checking / Misinformation Detection (NLP Focus)
• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Web Mining and Content Analysis: Content-based information diffusion
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience

Abstract

Although news negativity is often studied, missing is comparative evidence on the prevalence of and engagement with negative political and non-political news posts on social media. We use 6,081,134 Facebook posts published between January 1, 2020, and April 1, 2024, by 97 media organizations in six countries (U.S., UK, Ireland, Poland, France, Spain) and develop two multilingual classifiers for labeling posts as (non-)political and (non-)negative. We show that: (1) negative news posts constitute a relatively small fraction (12.6%); (2) political news posts are neither more nor less negative than non-political news posts; (3) U.S. political news posts are less negative relative to the other countries on average (40% lower odds); (4) Negative news posts get 15% fewer likes and 13% fewer comments than non-negative news posts. Lastly, (5) we provide estimates of the proportion of the total volume of user engagement with negative news posts and show that only between 10.2% to 13.1% of engagement is linked to negative posts by the analyzed news organizations.

Problem

• Analyzing prevalence of negative vs non-negative news posts
• Comparing engagement levels with political and non-political news
• Assessing cross-country differences in negativity of news content

Innovation

• Multilingual classifiers for news labeling
• Large-scale Facebook posts analysis
• Comparative engagement metrics for negativity