A Sentiment Analysis Dataset for Code-Mixed Malayalam-English

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

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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/teach-a-man-to-fish/2020.sltu-1.25.pdf
Code
 bharathichezhiyan/MalayalamMixSentiment
Data
MalayalamMixSentiment