On the Presence of Abusive Language in Mis/Disinformation.

The rise in mis/disinformation and abusive language online is alarming. These problems threaten society, impacting users’ mental health and even politics and democracy. Social science studies have already theorized about those problems’ mutual spread, for instance, regarding how users interact with mis/disinformation. In this work, we propose to analyze news articles’ production patterns instead of the consumption perspective, focusing on the textual news content. We perform a textual analysis of online news and conclude that false news present a higher prevalence of abusive language when compared to real news. The found patterns are consistent across datasets, even when they belong to different topics. To better understand these differences, we analyze psycholinguistic patterns of false and real news writings. Finally, we analyze which news categories are more affected by abusive language.