Mandl, T, Modha, S, Shahi, GK et al. (5 more authors) (2020) Overview of the HASOC track at FIRE 2020: Hate speech and offensive content identification in Indo-European languages. In: CEUR Workshop Proceedings. Forum for Information Retrieval Evaluation,, 16-20 Dec 2020, Hyderabad, India. CEUR Workshop Proceedings , pp. 87-111.
Abstract
With the growth of social media, the spread of hate speech is also increasing rapidly. Social media are widely used in many countries. Also Hate Speech is spreading in these countries. This brings a need for multilingual Hate Speech detection algorithms. Much research in this area is dedicated to English at the moment. The HASOC track intends to provide a platform to develop and optimize Hate Speech detection algorithms for Hindi, German and English. The dataset is collected from a Twitter archive and pre-classified by a machine learning system. HASOC has two sub-task for all three languages: task A is a binary classification problem (Hate and Not Offensive) while task B is a fine-grained classification problem for three classes (HATE) Hate speech, OFFENSIVE and PROFANITY. Overall, 252 runs were submitted by 40 teams. The performance of the best classification algorithms for task A are F1 measures of 0.51, 0.53 and 0.52 for English, Hindi, and German, respectively. For task B, the best classification algorithms achieved F1 measures of 0.26, 0.33 and 0.29 for English, Hindi, and German, respectively. This article presents the tasks and the data development as well as the results. The best performing algorithms were mainly variants of the transformer architecture BERT. However, also other systems were applied with good success.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Copyright for this paper by its authors.Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). |
Keywords: | Hate speech, Offensive Language, Multilingual Text Classification, Online Harm, Machine Learning, Evaluation,BERT |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Apr 2021 10:20 |
Last Modified: | 23 Apr 2021 10:20 |
Status: | Published |
Publisher: | CEUR Workshop Proceedings |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:173377 |