Dynamics of online hate and misinformation

In this research on the online hate speech trends, the authors have been able to highlight how online hate speech develops. Using a a machine learning model, trained and fine-tuned on a large set of hand-annotated data, authors draw the following conclusions:

• there is no evidence of the presence of “pure haters”, meant as active users posting exclusively hateful comments;

• users skewed towards one of the two categories of video channels (questionable, reliable) are more prone to use inappropriate, violent, or hateful language within their opponents’ community;

• users loyal to reliable sources use on average a more toxic language than their counterpart;

• the overall toxicity of the discussion increases with its length, measured both in terms of the number of comments and time.

Language of the resource: English

Link to the resource: https://www.nature.com/articles/s41598-021-01487-w#Bib1