Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3083
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPanchendraraja, R-
dc.contributor.authorSaxena, A-
dc.date.accessioned2022-11-29T04:14:27Z-
dc.date.available2022-11-29T04:14:27Z-
dc.date.issued2022-09-19-
dc.identifier.citationPanchendrarajan, R., Saxena, A. (2022). Deep Learning for Code-Mixed Text Mining in Social Media: A Brief Review. In: Hong, TP., Serrano-Estrada, L., Saxena, A., Biswas, A. (eds) Deep Learning for Social Media Data Analytics. Studies in Big Data, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-031-10869-3_3en_US
dc.identifier.isbn978-3-031-10868-6-
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/3083-
dc.description.abstractThe advent of social media in day-to-day life has made communications between people more often and easier than ever before. Analyzing the content in social media has opened up a massive amount of research and commercial opportunities. However, the content in social media is noisy and multi-lingual, which postures computational challenges ahead. Especially, the non-native English speakers and writers tend to mix their native language with English while generating social media content. Thus it requires a comprehensive prepossessing of text, including the identification of language for many language processing applications. In the area of language processing, deep learning has shown to be very successful, and the latest research works have witnessed the adoption of deep learning solutions to cater to the challenges in analyzing code-mixed text. Here, we highlight a comprehensive study of deep learning techniques used for analyzing the code-mix text of social media to understand the state-of-the-art and existing research challenges. We will discuss several applications of code-mixed text analysis and future directions.en_US
dc.language.isoenen_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofseriesDeep Learning for Social Media Data Analytics;pp 45–63-
dc.subjectCode-mixen_US
dc.subjectText miningen_US
dc.subjectDeep learningen_US
dc.subjectNatural language processingen_US
dc.subjectSocial mediaen_US
dc.titleDeep Learning for Code-Mixed Text Mining in Social Media: A Brief Reviewen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1007/978-3-031-10869-3_3en_US
Appears in Collections:Department of Computer Systems Engineering
Research Papers - Dept of Computer Systems Engineering
Research Papers - SLIIT Staff Publications

Files in This Item:
File Description SizeFormat 
Deep Learning for Social Media Data Analytics (Tzung-Pei Hong, Leticia Serrano-Estrada etc.).pdf
  Until 2050-12-31
415.98 kBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.