DravidianCodeMix: sentiment analysis and offensive language identification dataset for Dravidian languages in code-mixed text

Author:

Chakravarthi Bharathi RajaORCID,Priyadharshini Ruba,Muralidaran Vigneshwaran,Jose Navya,Suryawanshi Shardul,Sherly Elizabeth,McCrae John P.

Abstract

AbstractThis paper describes the development of a multilingual, manually annotated dataset for three under-resourced Dravidian languages generated from social media comments. The dataset was annotated for sentiment analysis and offensive language identification for a total of more than 60,000 YouTube comments. The dataset consists of around 44,000 comments in Tamil-English, around 7000 comments in Kannada-English, and around 20,000 comments in Malayalam-English. The data was manually annotated by volunteer annotators and has a high inter-annotator agreement in Krippendorff’s alpha. The dataset contains all types of code-mixing phenomena since it comprises user-generated content from a multilingual country. We also present baseline experiments to establish benchmarks on the dataset using machine learning and deep learning methods. The dataset is available on Github and Zenodo.

Funder

Science Foundation Ireland

Irish Research Council

National University Ireland, Galway

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Linguistics and Language,Education,Language and Linguistics

Reference83 articles.

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