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arXiv · 2006.00210

A Sentiment Analysis Dataset for Code-Mixed Malayalam-English

Bharathi Raja Chakravarthi·Navya Jose·Shardul Suryawanshi·Elizabeth Sherly·John P. 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.

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Bharathi Raja Chakravarthi, Navya Jose, Shardul Suryawanshi, Elizabeth Sherly, John P. McCrae. 2020-05-30. A Sentiment Analysis Dataset for Code-Mixed Malayalam-English. https://arxiv.org/abs/2006.00210

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