Resources and benchmark corpora for hate speech detection: a systematic review
Hate Speech in social media is a complex phenomenon, whose detection has recently
gained significant traction in the Natural Language Processing community, as attested by …
gained significant traction in the Natural Language Processing community, as attested by …
Handling bias in toxic speech detection: A survey
Detecting online toxicity has always been a challenge due to its inherent subjectivity. Factors
such as the context, geography, socio-political climate, and background of the producers …
such as the context, geography, socio-political climate, and background of the producers …
SemEval-2020 task 12: Multilingual offensive language identification in social media (OffensEval 2020)
We present the results and main findings of SemEval-2020 Task 12 on Multilingual
Offensive Language Identification in Social Media (OffensEval 2020). The task involves …
Offensive Language Identification in Social Media (OffensEval 2020). The task involves …
Comparing pre-trained language models for Spanish hate speech detection
Nowadays, due to the great uncontrolled content posted daily on the Web, there has also
been a huge increase in the dissemination of hate speech worldwide. Social media, blogs …
been a huge increase in the dissemination of hate speech worldwide. Social media, blogs …
A corpus of Turkish offensive language on social media
Ç Çöltekin - Proceedings of the Twelfth language resources and …, 2020 - aclanthology.org
This paper introduces a corpus of Turkish offensive language. To our knowledge, this is the
first corpus of offensive language for Turkish. The corpus consists of randomly sampled …
first corpus of offensive language for Turkish. The corpus consists of randomly sampled …
Evaluating aggression identification in social media
In this paper, we present the report and findings of the Shared Task on Aggression and
Gendered Aggression Identification organised as part of the Second Workshop on Trolling …
Gendered Aggression Identification organised as part of the Second Workshop on Trolling …
Implicitly abusive language–what does it actually look like and why are we not getting there?
Abusive language detection is an emerging field in natural language processing which has
received a large amount of attention recently. Still the success of automatic detection is …
received a large amount of attention recently. Still the success of automatic detection is …
Overview of the GermEval 2021 shared task on the identification of toxic, engaging, and fact-claiming comments
We present the GermEval 2021 shared task on the identification of toxic, engaging, and fact-
claiming comments. This shared task comprises three binary classification subtasks with the …
claiming comments. This shared task comprises three binary classification subtasks with the …
Detecting ethnicity-targeted hate speech in Russian social media texts
Ethnicity-targeted hate speech has been widely shown to influence on-the-ground inter-
ethnic conflict and violence, especially in such multi-ethnic societies as Russia. Therefore …
ethnic conflict and violence, especially in such multi-ethnic societies as Russia. Therefore …
Time of your hate: The challenge of time in hate speech detection on social media
The availability of large annotated corpora from social media and the development of
powerful classification approaches have contributed in an unprecedented way to tackle the …
powerful classification approaches have contributed in an unprecedented way to tackle the …