Home > Research > Publications & Outputs > Overview of the HASOC Subtrack at FIRE 2021

Research

Links

Text available via DOI:

View graph of relations

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

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Published

Standard

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; Shahi, Gautam Kishore ; Mandl, Thomas et al.
Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation. New York: Association for Computing Machinery (ACM), 2022. p. 1-3.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Modha, S, Shahi, GK, Mandl, T, 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 Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation. Association for Computing Machinery (ACM), New York, pp. 1-3, 13th Annual Meeting of the Forum for Information Retrieval Evaluation, 13/12/21. https://doi.org/10.1145/3503162.3503176

APA

Modha, S., Shahi, G. K., Mandl, T., 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 Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation (pp. 1-3). Association for Computing Machinery (ACM). https://doi.org/10.1145/3503162.3503176

Vancouver

Modha S, Shahi GK, Mandl T, 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 Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation. New York: Association for Computing Machinery (ACM). 2022. p. 1-3 Epub 2021 Dec 13. doi: 10.1145/3503162.3503176

Author

Modha, Sandip ; Shahi, Gautam Kishore ; Mandl, Thomas 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. Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation. New York : Association for Computing Machinery (ACM), 2022. pp. 1-3

Bibtex

@inproceedings{669b85b78257462aabe2a116983d5761,
title = "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 = "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 Shahi, {Gautam Kishore} and Thomas Mandl and Hiren Madhu and Shrey Satapara and Tharindu Ranasinghe and Marcos Zampieri",
year = "2022",
month = jan,
day = "26",
doi = "10.1145/3503162.3503176",
language = "English",
pages = "1--3",
booktitle = "Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation",
publisher = "Association for Computing Machinery (ACM)",
address = "United States",
note = "13th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE ; Conference date: 13-12-2021 Through 17-12-2021",

}

RIS

TY - GEN

T1 - Overview of the HASOC Subtrack at FIRE 2021

T2 - 13th Annual Meeting of the Forum for Information Retrieval Evaluation

AU - Modha, Sandip

AU - Shahi, Gautam Kishore

AU - Mandl, Thomas

AU - Madhu, Hiren

AU - Satapara, Shrey

AU - Ranasinghe, Tharindu

AU - Zampieri, Marcos

PY - 2022/1/26

Y1 - 2022/1/26

N2 - 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.

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.

U2 - 10.1145/3503162.3503176

DO - 10.1145/3503162.3503176

M3 - Conference contribution/Paper

SP - 1

EP - 3

BT - Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation

PB - Association for Computing Machinery (ACM)

CY - New York

Y2 - 13 December 2021 through 17 December 2021

ER -