MUDES: Multilingual Detection of Offensive Spans


The interest in offensive content identification in social media has grown substantially in recent years. Previous work has dealt mostly with post level annotations. However, identifying offensive spans is useful in many ways. To help coping with this important challenge, we present MUDES, a multilingual system to detect offensive spans in texts. MUDES features pre-trained models, a Python API for developers, and a user-friendly web-based interface. A detailed description of MUDES’ components is presented in this paper.

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Event Title: 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations
Event Type: Other
Event Location: online
Event Dates: 2021-06-06 - 2021-06-11
Last Modified: 27 Dec 2023 10:11
Date Deposited: 24 Jan 2023 16:09
Full Text Link: https://www.len ... 626-734-968-800
https://aclanth ... naacl-demos.17/
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PURE Output Type: Conference contribution
Published Date: 2021-06
Authors: Ranasinghe, Tharindu (ORCID Profile 0000-0003-3207-3821)
Zampieri, Marcos



Version: Published Version

License: Creative Commons Attribution

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