Dynamics of online hate and misinformation

Online debates are often characterised by extreme polarisation and heated discussions among users. The presence of hate speech online is becoming increasingly problematic, making necessary the development of appropriate countermeasures. In this work, we perform hate speech detection on a corpus of m...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Scientific reports Ročník 11; číslo 1; s. 22083 - 12
Hlavní autori: Cinelli, Matteo, Pelicon, Andraž, Mozetič, Igor, Quattrociocchi, Walter, Novak, Petra Kralj, Zollo, Fabiana
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Nature Publishing Group UK 11.11.2021
Nature Publishing Group
Nature Portfolio
Predmet:
639/705/117
639/705/258
Hate speech
Humanities and Social Sciences
Language
Learning algorithms
Machine learning
multidisciplinary
Science
Science (multidisciplinary)
ISSN:2045-2322, 2045-2322
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Online debates are often characterised by extreme polarisation and heated discussions among users. The presence of hate speech online is becoming increasingly problematic, making necessary the development of appropriate countermeasures. In this work, we perform hate speech detection on a corpus of more than one million comments on YouTube videos through a machine learning model, trained and fine-tuned on a large set of hand-annotated data. Our analysis shows that there is no evidence of the presence of “pure haters”, meant as active users posting exclusively hateful comments. Moreover, coherently with the echo chamber hypothesis, we find that 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. Interestingly, users loyal to reliable sources use on average a more toxic language than their counterpart. Finally, we find that the overall toxicity of the discussion increases with its length, measured both in terms of the number of comments and time. Our results show that, coherently with Godwin’s law, online debates tend to degenerate towards increasingly toxic exchanges of views.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-021-01487-w