JOURNAL ARTICLE

Zero-shot cross-lingual content filtering: offensive language and hate speech detection

Andraž, PeliconShekhar, RaviMartinc, MatejŠkrlj, BlažPollak, SenjaPurver, Matthew

Year: 2021 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

We present a system for zero-shot crosslingual offensive language and hate speech classification. The system was trained on English datasets and tested on a task of detecting hate speech and offensive social media content in a number of languages without any additional training. Experiments show an impressive ability of both models to generalize from English to other languages. There is however an expected gap in performance between the tested cross-lingual models and the monolingual models. The best performing model (offensive content classifier) is available online as a REST API

Keywords:
Offensive Voice activity detection Task (project management) Content (measure theory) Language identification Factor (programming language)

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Topics

Hate Speech and Cyberbullying Detection
Physical Sciences →  Computer Science →  Artificial Intelligence
Spam and Phishing Detection
Physical Sciences →  Computer Science →  Information Systems
Bullying, Victimization, and Aggression
Social Sciences →  Psychology →  Social Psychology
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