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Aggression Identification

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.

Papers

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Showing 1–10 of 27 papers

TitleStatusHype
Aggression and Misogyny Detection using BERT: A Multi-Task ApproachCode1
Bias, Threat and Aggression Identification Using Machine Learning Techniques on Multilingual Comments—0
ComMA@ICON: Multilingual Gender Biased and Communal Language Identification Task at ICON-2021—0
The ComMA Dataset V0.2: Annotating Aggression and Bias in Multilingual Social Media Discourse—0
Controversy and Conformity: from Generalized to Personalized Aggressiveness DetectionCode0
Aggression Identification in English, Hindi and Bangla Text using BERT, RoBERTa and SVMCode0
Evaluating Aggression Identification in Social Media—0
Bagging BERT Models for Robust Aggression IdentificationCode0
Aggression Identification in Social Media: a Transfer Learning Based Approach—0
AI\_ML\_NIT\_Patna @ TRAC - 2: Deep Learning Approach for Multi-lingual Aggression Identification—0
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