The present paper introduces new sentiment data, MaCMS, for Magahi-Hindi-English (MHE) code-mixed language, where Magahi is a less-resourced minority language. This dataset is the first Magahi-Hindi-English code-mixed dataset for sentiment analysis tasks. Further, we also provide a linguistics analysis of the dataset to understand the structure of code-mixing and a statistical study to understand the language preferences of speakers with different polarities. With these analyses, we also train baseline models to evaluate the dataset's quality.
Cite
@article{arxiv.2403.04639,
title = {MaCmS: Magahi Code-mixed Dataset for Sentiment Analysis},
author = {Priya Rani and Gaurav Negi and Theodorus Fransen and John P. McCrae},
journal= {arXiv preprint arXiv:2403.04639},
year = {2024}
}