Aggression Identification
6 papers with code • 0 benchmarks • 2 datasets
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
These leaderboards are used to track progress in Aggression Identification
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Latest papers with no code
The ComMA Dataset V0.2: Annotating Aggression and Bias in Multilingual Social Media Discourse
In this paper, we discuss the development of a multilingual dataset annotated with a hierarchical, fine-grained tagset marking different types of aggression and the "context" in which they occur.
Evaluating Aggression Identification in Social Media
The task consisted of two sub-tasks - aggression identification (sub-task A) and gendered identification (sub-task B) - in three languages - Bangla, Hindi and English.
Aggression Identification in Social Media: a Transfer Learning Based Approach
The evaluation part of this paper is based on the dataset provided by the TRAC shared task (Kumar et al., 2018a).
IRIT at TRAC 2020
This paper describes the participation of the IRIT team in the TRAC (Trolling, Aggression and Cyberbullying) 2020 shared task (Bhattacharya et al., 2020) on Aggression Identification and more precisely to the shared task in English language.
Scmhl5 at TRAC-2 Shared Task on Aggression Identification: Bert Based Ensemble Learning Approach
This paper presents a system developed during our participation (team name: scmhl5) in the TRAC-2 Shared Task on aggression identification.
The Role of Computational Stylometry in Identifying (Misogynistic) Aggression in English Social Media Texts
In this paper, we describe UniOr{\_}ExpSys team participation in TRAC-2 (Trolling, Aggression and Cyberbullying) shared task, a workshop organized as part of LREC 2020.
FlorUniTo@TRAC-2: Retrofitting Word Embeddings on an Abusive Lexicon for Aggressive Language Detection
This paper describes our participation to the TRAC-2 Shared Tasks on Aggression Identification.
AI\_ML\_NIT\_Patna @ TRAC - 2: Deep Learning Approach for Multi-lingual Aggression Identification
This paper describes the details of developed models and results of team AI{\_}ML{\_}NIT{\_}Patna for the shared task of TRAC - 2.
A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts
To solve these problems, we have introduced a unified and robust multi-modal deep learning architecture which works for English code-mixed dataset and uni-lingual English dataset both. The devised system, uses psycho-linguistic features and very ba-sic linguistic features.
Benchmarking Aggression Identification in Social Media
For this task, the participants were provided with a dataset of 15, 000 aggression-annotated Facebook Posts and Comments each in Hindi (in both Roman and Devanagari script) and English for training and validation.
