A Sentiment Analysis Dataset for Code-Mixed Malayalam-English

Bharathi Raja Chakravarthi, Navya Jose, Shardul Suryawanshi, Elizabeth Sherly, John Philip McCrae

Abstract
There is an increasing demand for sentiment analysis of text from social media which are mostly code-mixed. Systems trained on monolingual data fail for code-mixed data due to the complexity of mixing at different levels of the text. However, very few resources are available for code-mixed data to create models specific for this data. Although much research in multilingual and cross-lingual sentiment analysis has used semi-supervised or unsupervised methods, supervised methods still performs better. Only a few datasets for popular languages such as English-Spanish, English-Hindi, and English-Chinese are available. There are no resources available for Malayalam-English code-mixed data. This paper presents a new gold standard corpus for sentiment analysis of code-mixed text in Malayalam-English annotated by voluntary annotators. This gold standard corpus obtained a Krippendorff’s alpha above 0.8 for the dataset. We use this new corpus to provide the benchmark for sentiment analysis in Malayalam-English code-mixed texts.
Anthology ID:
2020.sltu-1.25
Volume:
Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Dorothee Beermann, Laurent Besacier, Sakriani Sakti, Claudia Soria
Venue:
SLTU
SIG:
Publisher:
European Language Resources association
Note:
Pages:
177–184
Language:
English
URL:
https://aclanthology.org/2020.sltu-1.25
DOI:
Bibkey:
Cite (ACL):
Bharathi Raja Chakravarthi, Navya Jose, Shardul Suryawanshi, Elizabeth Sherly, and John Philip McCrae. 2020. A Sentiment Analysis Dataset for Code-Mixed Malayalam-English. In Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL), pages 177–184, Marseille, France. European Language Resources association.
Cite (Informal):
A Sentiment Analysis Dataset for Code-Mixed Malayalam-English (Chakravarthi et al., SLTU 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingest-2024-clasp/2020.sltu-1.25.pdf
Code
 bharathichezhiyan/MalayalamMixSentiment
Data
MalayalamMixSentiment
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