A survey cataloging datasets, features, and machine-learning methods for automatic hate speech detection in low-resource languages, organized by world region, with an overview of open challenges.
Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
The widespread presence of offensive language on social media motivated the development of systems capable of recognizing such content automatically. Apart from a few notable exceptions, most research on automatic offensive language identification has dealt with English. To address this shortcoming, we introduce MOLD, the Marathi Offensive Language Dataset. MOLD is the first dataset of its kind compiled for Marathi, thus opening a new domain for research in low-resource Indo-Aryan languages. We present results from several machine learning experiments on this dataset, including zero-short and other transfer learning experiments on state-of-the-art cross-lingual transformers from existing data in Bengali, English, and Hindi.
fields
cs.CL 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
A Survey on Automatic Online Hate Speech Detection in Low-Resource Languages
A survey cataloging datasets, features, and machine-learning methods for automatic hate speech detection in low-resource languages, organized by world region, with an overview of open challenges.