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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 DravidianCodeMix: Sentiment Analysis and Offensive Language Identification Dataset for Dravidian Languages in Code-Mixed Text ... Chakravarthi, Bharathi Raja; Priyadharshini, Ruba; Muralidaran, Vigneshwaran. - : Zenodo, 2021 BASE Show details 2 DravidianCodeMix: Sentiment Analysis and Offensive Language Identification Dataset for Dravidian Languages in Code-Mixed Text ... Chakravarthi, Bharathi Raja; Priyadharshini, Ruba; Muralidaran, Vigneshwaran. - : Zenodo, 2021 BASE Show details 3 DravidianCodeMix: Sentiment Analysis and Offensive Language Identification Dataset for Dravidian Languages in Code-Mixed Text ... Chakravarthi, Bharathi Raja; Priyadharshini, Ruba; Muralidaran, Vigneshwaran. - : arXiv, 2021 BASE Show details 4 A sentiment analysis dataset for code-mixed Malayalam-English Sherly, Elizabeth; Jose, Navya; McCrae, John P.; Chakravarthi, Bharathi Raja; Suryawanshi, Shardul. - : European Language Resources Association (ELRA), 2020 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 ; This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight), SFI/12/RC/2289 P2 (Insight 2), co-funded by the European Regional Development Fund as well as by the EU H2020 programme under grant agreements 731015 (ELEXIS-European Lexical Infrastructure), 825182 (Pret- ˆ a-LLOD), and Irish Research Council ` grant IRCLA/2017/129 (CARDAMOM-Comparative Deep Models of Language for Minority and Historical Languages). ; non-peer-reviewed Keyword: code-mixing; dataset; Malayalam; sentiment analysis URL: http://hdl.handle.net/10379/16103 BASE Hide details 5 A survey of current datasets for code-switching research Jose, Navya; Chakravarthi, Bharathi Raja; Suryawanshi, Shardul. - : IEEE, 2020 BASE Show details 6 A Sentiment Analysis Dataset for Code-Mixed Malayalam-English ... Chakravarthi, Bharathi Raja; Jose, Navya; Suryawanshi, Shardul. - : arXiv, 2020 BASE Show details 7 A Sentiment Analysis Dataset for Code-Mixed Malayalam-English ... Chakravarthi, Bharathi Raja; Jose, Navya; Suryawanshi, Shardul. - : Zenodo, 2020 BASE Show details 8 A Sentiment Analysis Dataset for Code-Mixed Malayalam-English ... Chakravarthi, Bharathi Raja; Jose, Navya; Suryawanshi, Shardul. - : Zenodo, 2020 BASE Show details

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