2025/07/25 by Szymon Talaga, Dominik Batorski, Talaga, Szymon +3
Computer Science · Social Sciences · #Content analysis #FOS: Computer and information sciences #Machine Learning (cs.LG) #Misinformation and Its Impacts #Negativity effect #News media #Politics #Sentiment Analysis and Opinion Mining #Social Media and Politics #Social and Information Networks (cs.SI) #Social media #User engagement
paper · pdf · doi:10.48550/arxiv.2507.19300
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2025/07/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.