Overview of the HASOC Subtrack at FIRE 2021:: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages and Conversational Hate Speech

Sandip Modha; Thomas Mandl; Gautam Kishore Shahi; Hiren Madhu; Shrey Satapara; T. Ranasinghe; Marcos Zampieri

doi:10.1145/3503162.3503176

Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages and Conversational Hate Speech

Sandip Modha, Thomas Mandl, Gautam Kishore Shahi, Hiren Madhu, Shrey Satapara, T. Ranasinghe, Marcos Zampieri

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

The HASOC track is dedicated to the evaluation of technology for finding Offensive Language and Hate Speech. HASOC is creating a multilingual data corpus mainly for English and under-resourced languages(Hindi and Marathi). This paper presents one HASOC subtrack with two tasks. In 2021, we organized the classification task for English, Hindi, and Marathi. The first task consists of two classification tasks; Subtask 1A consists of a binary and fine-grained classification into offensive and non-offensive tweets. Subtask 1B asks to classify the tweets into Hate, Profane and offensive. Task 2 consists of identifying tweets given additional context in the form of the preceding conversion. During the shared task, 65 teams have submitted 652 runs. This overview paper briefly presents the task descriptions, the data and the results obtained from the participant’s submission.

Original language	English
Title of host publication	FIRE '21:
Subtitle of host publication	Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation
Publisher	ACM
Number of pages	3
ISBN (Electronic)	978-1-4503-9596-0
DOIs	https://doi.org/10.1145/3503162.3503176
Publication status	Published - 26 Jan 2022
Event	FIRE 2021: Forum for Information Retrieval Evaluation - Online, India Duration: 13 Dec 2021 → 17 Dec 2021 http://fire.irsi.res.in/fire/2021/home

Conference

Conference	FIRE 2021: Forum for Information Retrieval Evaluation
Abbreviated title	FIRE 2021
Country/Territory	India
Period	13/12/21 → 17/12/21
Internet address	http://fire.irsi.res.in/fire/2021/home

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10.1145/3503162.3503176

Cite this

Modha, S., Mandl, T., Shahi, G. K., Madhu, H., Satapara, S., Ranasinghe, T., & Zampieri, M. (2022). Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages and Conversational Hate Speech. In FIRE '21: : Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation ACM. https://doi.org/10.1145/3503162.3503176

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abstract = "The HASOC track is dedicated to the evaluation of technology for finding Offensive Language and Hate Speech. HASOC is creating a multilingual data corpus mainly for English and under-resourced languages(Hindi and Marathi). This paper presents one HASOC subtrack with two tasks. In 2021, we organized the classification task for English, Hindi, and Marathi. The first task consists of two classification tasks; Subtask 1A consists of a binary and fine-grained classification into offensive and non-offensive tweets. Subtask 1B asks to classify the tweets into Hate, Profane and offensive. Task 2 consists of identifying tweets given additional context in the form of the preceding conversion. During the shared task, 65 teams have submitted 652 runs. This overview paper briefly presents the task descriptions, the data and the results obtained from the participant{\textquoteright}s submission.",

author = "Sandip Modha and Thomas Mandl and Shahi, {Gautam Kishore} and Hiren Madhu and Shrey Satapara and T. Ranasinghe and Marcos Zampieri",

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booktitle = "FIRE '21:",

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Modha, S, Mandl, T, Shahi, GK, Madhu, H, Satapara, S, Ranasinghe, T & Zampieri, M 2022, Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages and Conversational Hate Speech. in FIRE '21: : Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation. ACM, FIRE 2021: Forum for Information Retrieval Evaluation, India, 13/12/21. https://doi.org/10.1145/3503162.3503176

Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages and Conversational Hate Speech. / Modha, Sandip; Mandl, Thomas; Shahi, Gautam Kishore et al.
FIRE '21: : Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation. ACM, 2022.

Research output: Chapter in Book/Published conference output › Conference publication

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AU - Shahi, Gautam Kishore

AU - Madhu, Hiren

AU - Satapara, Shrey

AU - Ranasinghe, T.

AU - Zampieri, Marcos

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AB - The HASOC track is dedicated to the evaluation of technology for finding Offensive Language and Hate Speech. HASOC is creating a multilingual data corpus mainly for English and under-resourced languages(Hindi and Marathi). This paper presents one HASOC subtrack with two tasks. In 2021, we organized the classification task for English, Hindi, and Marathi. The first task consists of two classification tasks; Subtask 1A consists of a binary and fine-grained classification into offensive and non-offensive tweets. Subtask 1B asks to classify the tweets into Hate, Profane and offensive. Task 2 consists of identifying tweets given additional context in the form of the preceding conversion. During the shared task, 65 teams have submitted 652 runs. This overview paper briefly presents the task descriptions, the data and the results obtained from the participant’s submission.

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Modha S, Mandl T, Shahi GK, Madhu H, Satapara S, Ranasinghe T et al. Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages and Conversational Hate Speech. In FIRE '21: : Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation. ACM. 2022 doi: 10.1145/3503162.3503176

Overview of the HASOC Subtrack at FIRE 2021: Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages and Conversational Hate Speech

Abstract

Conference

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