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 outputConference publication


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 languageEnglish
Title of host publicationFIRE '21:
Subtitle of host publicationProceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation
Number of pages3
ISBN (Electronic)978-1-4503-9596-0
Publication statusPublished - 26 Jan 2022
EventFIRE 2021: Forum for Information Retrieval Evaluation - Online, India
Duration: 13 Dec 202117 Dec 2021


ConferenceFIRE 2021: Forum for Information Retrieval Evaluation
Abbreviated titleFIRE 2021
Internet address

Cite this