@inproceedings{maimaitituoheti-2022-ablimet,
    title = "{ABLIMET} @{LT}-{EDI}-{ACL}2022: A Roberta based Approach for Homophobia/Transphobia Detection in Social Media",
    author = "Maimaitituoheti, Abulimiti",
    editor = "Chakravarthi, Bharathi Raja  and
      Bharathi, B  and
      McCrae, John P  and
      Zarrouk, Manel  and
      Bali, Kalika  and
      Buitelaar, Paul",
    booktitle = "Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/2022.ltedi-1.19/",
    doi = "10.18653/v1/2022.ltedi-1.19",
    pages = "155--160",
    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 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."
}