Hate Speech Detection
Hate Speech Detection is a crucial task in the field of Natural Language Processing, aimed at identifying and detecting hate speech and violent tendencies in communications such as text and audio. This task evaluates biases based on protected characteristics like race, gender, sexual orientation, religion, age, etc., and common evaluation metrics include F-score or F-measure. Its application value lies in maintaining a healthy and safe online environment, preventing the spread of harmful information.
Ethos Binary
BiLSTM+Attention+FT
HateXplain
BERT-MRP
Ethos MultiLabel
MLARAM
Waseem et al., 2018
Mozafari et al., 2019
AbusEval
HateBERT
Automatic Misogynistic Identification
mBert
HateMM
HXP + CLAP + CLIP
HatEval
OffensEval 2019
HateBERT
ToLD-Br
Multilingual BERT
bajer_danish_misogyny
AOM mBERT
DKhate
Baseline
Hostility Detection Dataset in Hindi
Auxiliary IndicBert
OLID
RoBERTa-large-ST
SHAJ