About
Develop a classifier that could make a 3-way classification in-between ‘Overtly Aggressive’, ‘Covertly Aggressive’ and ‘Non-aggressive’ text data. For this, TRAC-2 dataset of 5,000 aggression-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
Greatest papers with code
Aggression and Misogyny Detection using BERT: A Multi-Task Approach
LREC 2020
• NiloofarSafi/TRAC-2
• 
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).
ABUSIVE LANGUAGE AGGRESSION IDENTIFICATION HATE SPEECH DETECTION MISOGYNISTIC AGGRESSION IDENTIFICATION MULTI-TASK LEARNING
Aggression Identification in English, Hindi and Bangla Text using BERT, RoBERTa and SVM
LREC 2020
• cozek/trac2020_submission
•
In our study, we used English BERT (En-BERT), RoBERTa, DistilRoBERTa, and SVM based classifiers for English language.
AGGRESSION IDENTIFICATION MISOGYNISTIC AGGRESSION IDENTIFICATION
Aggressive Language Identification Using Word Embeddings and Sentiment Features
Several machine learning methods and different combinations of features were tried.
AGGRESSION IDENTIFICATION LANGUAGE IDENTIFICATION WORD EMBEDDINGS