Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/23086
Title: Sentiment classification of Sinhala content in social media
Authors: Jayasuriya, Pradeep
Ekanayake, Sarith
Munasinghe, Ranjiva
Kumarasinghe, Bihara
Weerasinghe, Isuru
Thelijjagoda, Samantha
Keywords: Machine Learning, Natural Language Processing, Sentiment Analysis, Social Media, Supervised Learning
Issue Date: 2020
Publisher: Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka
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.
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.
URI: http://repository.kln.ac.lk/handle/123456789/23086
Appears in Collections:Smart Computing and Systems Engineering - 2020 (SCSE 2020)

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