Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Sentiment Analysis Dataset for Code-Mixed Malayalam-English   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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The categories of this paper are: ao-sci
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The categories of this paper are: math-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: acc-phys
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-th
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The categories of this paper are: math
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The categories of this paper are: nlin
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The categories of this paper are: q-bio
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The categories of this paper are: adap-org
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-fin
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The categories of this paper are: eess
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The categories of this paper are: hep-lat
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The categories of this paper are: hep-ph
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The categories of this paper are: solv-int