Sentiment classification of Sinhala content in social media

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Date

2020

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Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka

Abstract

In this study, we focus on the classification of Sinhala social media sentiments into positive and negative classes for a particular domain (sports). We have employed machine learning algorithms and lexicon-based sentiment classification methods. We also consider a hybrid approach by constructing an ensemble classifier in which we combine Machine Learning and Lexicon based methods. For individual methods, machine learning algorithms performed best in terms of accuracy. The ensemble classifier was able to improve performance further.

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Keywords

Machine Learning, Natural Language Processing, Sentiment Analysis, Social Media, Supervised Learning

Citation

Jayasuriya, Pradeep, Ekanayake, Sarith, Munasinghe, Ranjiva, Kumarasinghe, Bihara , Weerasinghe, Isuru and Thelijjagoda, Samantha (2020). Sentiment classification of Sinhala content in social media. In : International Research Conference on Smart Computing and Systems Engineering, 2020. Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka, p.136.

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