• Cinelli M., Pelicon A., Mozetic I., Quattrociocchi W., Novak Krali P., Zollo F.

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

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