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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
  • Sandip Modha
  • Gautam Kishore Shahi
  • Thomas Mandl
  • Hiren Madhu
  • Shrey Satapara
  • Tharindu Ranasinghe
  • Marcos Zampieri
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Publication date26/01/2022
Host publicationProceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1-3
Number of pages3
ISBN (electronic)9781450395960
<mark>Original language</mark>English
Event13th Annual Meeting of the Forum for Information Retrieval Evaluation -
Duration: 13/12/2021 → 17/12/2021

Conference

Conference13th Annual Meeting of the Forum for Information Retrieval Evaluation
Abbreviated titleFIRE
Period13/12/21 → 17/12/21

Conference

Conference13th Annual Meeting of the Forum for Information Retrieval Evaluation
Abbreviated titleFIRE
Period13/12/21 → 17/12/21

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.