Modeling Annotators’ Perspectives to improve Online Hate Detection

- 1 min
natural language processing deep learning hate speech detection computational social science

Hate Speech in social media and other online platforms is a pressing issue. This on-going research project is in collaboration with researchers from Queen Mary University of London, UK. The project aims at modeling annotators’ perspectives by generating annotator specific embeddings through machine learning models, along with the transformer models. Infusing different perspectives in ML models for subjective tasks like Hate Speech detection has the potential to improve the model’s performance.

Vibhor Agarwal

Vibhor Agarwal

PhD @University of Surrey, UK | Visiting Researcher @Georgia Tech, @QMUL | Interested in NLP, Graphs, and Computational Social Science | Ex-NLP Research @JP Morgan AI Research, SRE @Media.net, GSoC'18 @Oppia

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