@inproceedings{thapa-etal-2024-extended,
title = "Extended Multimodal Hate Speech Event Detection During {R}ussia-{U}kraine Crisis - Shared Task at {CASE} 2024",
author = {Thapa, Surendrabikram and
Rauniyar, Kritesh and
Jafri, Farhan and
Veeramani, Hariram and
Jain, Raghav and
Jain, Sandesh and
Vargas, Francielle and
H{\"u}rriyeto{\u{g}}lu, Ali and
Naseem, Usman},
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Tanev, Hristo and
Thapa, Surendrabikram and
Uludo{\u{g}}an, G{\"o}k{\c{c}}e},
booktitle = "Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.case-1.31",
pages = "221--228",
abstract = "Addressing the need for effective hate speech moderation in contemporary digital discourse, the Multimodal Hate Speech Event Detection Shared Task made its debut at CASE 2023, co-located with RANLP 2023. Building upon its success, an extended version of the shared task was organized at the CASE workshop in EACL 2024. Similar to the earlier iteration, in this shared task, participants address hate speech detection through two subtasks. Subtask A is a binary classification problem, assessing whether text-embedded images contain hate speech. Subtask B goes further, demanding the identification of hate speech targets, such as individuals, communities, and organizations within text-embedded images. Performance is evaluated using the macro F1-score metric in both subtasks. With a total of 73 registered participants, the shared task witnessed remarkable achievements, with the best F1-scores in Subtask A and Subtask B reaching 87.27{\%} and 80.05{\%}, respectively, surpassing the leaderboard of the previous CASE 2023 shared task. This paper provides a comprehensive overview of the performance of seven teams that submitted results for Subtask A and five teams for Subtask B.",
}
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<abstract>Addressing the need for effective hate speech moderation in contemporary digital discourse, the Multimodal Hate Speech Event Detection Shared Task made its debut at CASE 2023, co-located with RANLP 2023. Building upon its success, an extended version of the shared task was organized at the CASE workshop in EACL 2024. Similar to the earlier iteration, in this shared task, participants address hate speech detection through two subtasks. Subtask A is a binary classification problem, assessing whether text-embedded images contain hate speech. Subtask B goes further, demanding the identification of hate speech targets, such as individuals, communities, and organizations within text-embedded images. Performance is evaluated using the macro F1-score metric in both subtasks. With a total of 73 registered participants, the shared task witnessed remarkable achievements, with the best F1-scores in Subtask A and Subtask B reaching 87.27% and 80.05%, respectively, surpassing the leaderboard of the previous CASE 2023 shared task. This paper provides a comprehensive overview of the performance of seven teams that submitted results for Subtask A and five teams for Subtask B.</abstract>
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%0 Conference Proceedings
%T Extended Multimodal Hate Speech Event Detection During Russia-Ukraine Crisis - Shared Task at CASE 2024
%A Thapa, Surendrabikram
%A Rauniyar, Kritesh
%A Jafri, Farhan
%A Veeramani, Hariram
%A Jain, Raghav
%A Jain, Sandesh
%A Vargas, Francielle
%A Hürriyetoğlu, Ali
%A Naseem, Usman
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Thapa, Surendrabikram
%Y Uludoğan, Gökçe
%S Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024)
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F thapa-etal-2024-extended
%X Addressing the need for effective hate speech moderation in contemporary digital discourse, the Multimodal Hate Speech Event Detection Shared Task made its debut at CASE 2023, co-located with RANLP 2023. Building upon its success, an extended version of the shared task was organized at the CASE workshop in EACL 2024. Similar to the earlier iteration, in this shared task, participants address hate speech detection through two subtasks. Subtask A is a binary classification problem, assessing whether text-embedded images contain hate speech. Subtask B goes further, demanding the identification of hate speech targets, such as individuals, communities, and organizations within text-embedded images. Performance is evaluated using the macro F1-score metric in both subtasks. With a total of 73 registered participants, the shared task witnessed remarkable achievements, with the best F1-scores in Subtask A and Subtask B reaching 87.27% and 80.05%, respectively, surpassing the leaderboard of the previous CASE 2023 shared task. This paper provides a comprehensive overview of the performance of seven teams that submitted results for Subtask A and five teams for Subtask B.
%U https://aclanthology.org/2024.case-1.31
%P 221-228
Markdown (Informal)
[Extended Multimodal Hate Speech Event Detection During Russia-Ukraine Crisis - Shared Task at CASE 2024](https://aclanthology.org/2024.case-1.31) (Thapa et al., CASE-WS 2024)
ACL
- Surendrabikram Thapa, Kritesh Rauniyar, Farhan Jafri, Hariram Veeramani, Raghav Jain, Sandesh Jain, Francielle Vargas, Ali Hürriyetoğlu, and Usman Naseem. 2024. Extended Multimodal Hate Speech Event Detection During Russia-Ukraine Crisis - Shared Task at CASE 2024. In Proceedings of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2024), pages 221–228, St. Julians, Malta. Association for Computational Linguistics.