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LREC-COLING 2024main

MaCmS: Magahi Code-mixed Dataset for Sentiment Analysis

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

DOI:10.63317/4968zbuci46k

Abstract

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.

Details

Paper ID
lrec2024-main-0950
Pages
pp. 10880-10890
BibKey
rani-etal-2024-macms
Editor
N/A
Publisher
European Language Resources Association (ELRA) and ICCL
ISSN
2522-2686
ISBN
979-10-95546-34-4
Conference
Joint International Conference on Computational Linguistics, Language Resources and Evaluation
Location
Turin, Italy
Date
20 May 2024 25 May 2024

Authors

  • PR

    Priya Rani

  • GN

    Gaurav Negi

  • TF

    Theodorus Fransen

  • JM

    John P McCrae

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