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- W4225705554 abstract "Abstract This paper describes the development of a multilingual, manually annotated dataset for three under-resourced Dravidian languages generated from social media comments. The dataset was annotated for sentiment analysis and offensive language identification for a total of more than 60,000 YouTube comments. The dataset consists of around 44,000 comments in Tamil-English, around 7000 comments in Kannada-English, and around 20,000 comments in Malayalam-English. The data was manually annotated by volunteer annotators and has a high inter-annotator agreement in Krippendorff’s alpha. The dataset contains all types of code-mixing phenomena since it comprises user-generated content from a multilingual country. We also present baseline experiments to establish benchmarks on the dataset using machine learning and deep learning methods. The dataset is available on Github and Zenodo." @default.
- W4225705554 created "2022-05-05" @default.
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- W4225705554 date "2022-02-04" @default.
- W4225705554 modified "2023-10-02" @default.
- W4225705554 title "DravidianCodeMix: sentiment analysis and offensive language identification dataset for Dravidian languages in code-mixed text" @default.
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- W4225705554 doi "https://doi.org/10.1007/s10579-022-09583-7" @default.
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