Sentiment analysis for mixed script Indic sentences

dc.contributor.authorSharma, Yashvardhan
dc.date.accessioned2023-01-02T10:08:35Z
dc.date.available2023-01-02T10:08:35Z
dc.date.issued2016
dc.description.abstractIndia is a multi-lingual and multi-script country. Developing natural language processing techniques for Indic languages is an active area of research. With the advent of social media, there has been an increasing trend of mixing different languages to convey thoughts in social media text. Users are more comfortable in their regionalistic language and tend to express their thoughts by mixing words from multiple languages. In this paper, we have attempted to develop a system for mining sentiments from code mixed sentences for English with combination of four other Indian languages (Tamil, Telugu, Hindi and Bengali). Due to the complex nature of the problem the technique used is divided into two stages, viz Language Identification and Sentiment Mining Approach. Evaluated results are compared to baseline obtained from machine translated sentences in English, and found to be around 8% better in terms of precision. The proposed approach is flexible and robust enough to handle additional languages for identification as well as anomalous foreign or extraneous words.en_US
dc.identifier.urihttps://ieeexplore.ieee.org/document/7732099
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8215
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectComputer Scienceen_US
dc.subjectCode Mixeden_US
dc.subjectMixed Scriptingen_US
dc.subjectNatural Language Processingen_US
dc.subjectPolarityen_US
dc.titleSentiment analysis for mixed script Indic sentencesen_US
dc.typeArticleen_US

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