ABLIMET @LT-EDI-ACL2022: A RoBERTa based Approach for Homophobia/Transphobia Detection in Social Media

Abstract

This paper describes our system that participated in LT-EDI-ACL2022-Homophobia/Transphobia Detection in Social Media. Sexual minorities face a lot of unfair treatment and discrimination in our world. This creates enormous stress and many psychological problems for sexual minorities. There is a lot of hate speech on the internet, and homophobia/transphobia is one against sexual minorities. Identifying and processing homophobia/transphobia through natural language processing technology can improve the efficiency of processing it, and can quickly screen out it on the Internet. The organizer of the competition constructs a homophobia/transphobia detection dataset based on YouTube comments for English and Tamil. We use a RoBERTa-based approach to conduct our experiments on the dataset of the competition, and get better results.