@inproceedings{rajiakodi-etal-2024-overview,
title = "Overview of Shared Task on Caste and Migration Hate Speech Detection",
author = "Rajiakodi, Saranya and
Chakravarthi, Bharathi Raja and
Ponnusamy, Rahul and
Kumaresan, Prasanna and
Thangasamy, Sathiyaraj and
Sivagnanam, Bhuvaneswari and
Rajkumar, Charmathi",
editor = {Chakravarthi, Bharathi Raja and
B, Bharathi and
Buitelaar, Paul and
Durairaj, Thenmozhi and
Kov{\'a}cs, Gy{\"o}rgy and
Garc{\'\i}a Cumbreras, Miguel {\'A}ngel},
booktitle = "Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion",
month = mar,
year = "2024",
address = "St. Julian's, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.ltedi-1.14",
pages = "145--151",
abstract = "We present an overview of the first shared task on {``}Caste and Migration Hate Speech Detection.{''} The shared task is organized as part of LTEDI@EACL 2024. The system must delineate between binary outcomes, ascertaining whether the text is categorized as a caste/migration hate speech or not. The dataset presented in this shared task is in Tamil, which is one of the under-resource languages. There are a total of 51 teams participated in this task. Among them, 15 teams submitted their research results for the task. To the best of our knowledge, this is the first time the shared task has been conducted on textual hate speech detection concerning caste and migration. In this study, we have conducted a systematic analysis and detailed presentation of all the contributions of the participants as well as the statistics of the dataset, which is the social media comments in Tamil language to detect hate speech. It also further goes into the details of a comprehensive analysis of the participants{'} methodology and their findings.",
}
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<abstract>We present an overview of the first shared task on “Caste and Migration Hate Speech Detection.” The shared task is organized as part of LTEDI@EACL 2024. The system must delineate between binary outcomes, ascertaining whether the text is categorized as a caste/migration hate speech or not. The dataset presented in this shared task is in Tamil, which is one of the under-resource languages. There are a total of 51 teams participated in this task. Among them, 15 teams submitted their research results for the task. To the best of our knowledge, this is the first time the shared task has been conducted on textual hate speech detection concerning caste and migration. In this study, we have conducted a systematic analysis and detailed presentation of all the contributions of the participants as well as the statistics of the dataset, which is the social media comments in Tamil language to detect hate speech. It also further goes into the details of a comprehensive analysis of the participants’ methodology and their findings.</abstract>
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%0 Conference Proceedings
%T Overview of Shared Task on Caste and Migration Hate Speech Detection
%A Rajiakodi, Saranya
%A Chakravarthi, Bharathi Raja
%A Ponnusamy, Rahul
%A Kumaresan, Prasanna
%A Thangasamy, Sathiyaraj
%A Sivagnanam, Bhuvaneswari
%A Rajkumar, Charmathi
%Y Chakravarthi, Bharathi Raja
%Y B, Bharathi
%Y Buitelaar, Paul
%Y Durairaj, Thenmozhi
%Y Kovács, György
%Y García Cumbreras, Miguel Ángel
%S Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julian’s, Malta
%F rajiakodi-etal-2024-overview
%X We present an overview of the first shared task on “Caste and Migration Hate Speech Detection.” The shared task is organized as part of LTEDI@EACL 2024. The system must delineate between binary outcomes, ascertaining whether the text is categorized as a caste/migration hate speech or not. The dataset presented in this shared task is in Tamil, which is one of the under-resource languages. There are a total of 51 teams participated in this task. Among them, 15 teams submitted their research results for the task. To the best of our knowledge, this is the first time the shared task has been conducted on textual hate speech detection concerning caste and migration. In this study, we have conducted a systematic analysis and detailed presentation of all the contributions of the participants as well as the statistics of the dataset, which is the social media comments in Tamil language to detect hate speech. It also further goes into the details of a comprehensive analysis of the participants’ methodology and their findings.
%U https://aclanthology.org/2024.ltedi-1.14
%P 145-151
Markdown (Informal)
[Overview of Shared Task on Caste and Migration Hate Speech Detection](https://aclanthology.org/2024.ltedi-1.14) (Rajiakodi et al., LTEDI-WS 2024)
ACL
- Saranya Rajiakodi, Bharathi Raja Chakravarthi, Rahul Ponnusamy, Prasanna Kumaresan, Sathiyaraj Thangasamy, Bhuvaneswari Sivagnanam, and Charmathi Rajkumar. 2024. Overview of Shared Task on Caste and Migration Hate Speech Detection. In Proceedings of the Fourth Workshop on Language Technology for Equality, Diversity, Inclusion, pages 145–151, St. Julian's, Malta. Association for Computational Linguistics.