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

AbstractThis 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 the one against sexual minorities. Identifying and processing Homophobia/ Transphobia through natural language processing technology can improve the efficiency of processing Homophobia/ Transphobia, and can quickly screen out Homophobia/Transphobia on the Internet. The organizer of LT-EDI-ACL2022- Homophobia/Transphobia Detection in Social Media constructs a Homophobia/ Transphobia detection dataset based on YouTube comments for English and Tamil. We use a Roberta -based approach to conduct Homophobia/ Transphobia detection experiments on the dataset of the competition, and get better results.