Misogynistic Aggression Identification
2 papers with code • 0 benchmarks • 0 datasets
Develop a binary classifier for classifying the text as ‘gendered’ or ‘non-gendered’. For this, the TRAC-2 dataset of 5,000 annotated data from social media each in Bangla (in both Roman and Bangla script), Hindi (in both Roman and Devanagari script) and English for training and validation is to be used.
Benchmarks
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Most implemented papers
Aggression Identification in English, Hindi and Bangla Text using BERT, RoBERTa and SVM
cozek/trac2020_submission
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LREC 2020
In our study, we used English BERT (En-BERT), RoBERTa, DistilRoBERTa, and SVM based classifiers for English language.
Aggression and Misogyny Detection using BERT: A Multi-Task Approach
NiloofarSafi/TRAC-2
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LREC 2020
In recent times, the focus of the NLP community has increased towards offensive language, aggression, and hate-speech detection. This paper presents our system for TRAC-2 shared task on {``}Aggression Identification{''} (sub-task A) and {``}Misogynistic Aggression Identification{''} (sub-task B).
