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2021 NAACL NAACL 2021

MUDES: Multilingual Detection of Offensive Spans

Abstract

AbstractThe 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.

Authors

Tharindu Ranasinghe, Marcos Zampieri

Topics

Artificial Intelligence > Core AI > Multimodal Learning Machine Learning > Core Methods > Classification

Keywords

text classification multilingual nlp social media offensive content detection span detection
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