Twitter Sentiment Analysis of Movie Reviews using Ensemble Features Based Naïve Bayes

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Rosy Indah Permatasari, M. Ali Fauzi, Putra Pandu Adikara, Eka Dewi Lukmana Sari

2018 3rd International Conference on Sustainable Information Engineering and Technology, SIET 2018 - Proceedings Conference paper Cited by 23 Quartile

Abstract

Sentiment analysis or opinion mining is one of the latest research topics in the field of information processing. It aims to know whether the polarity of a text-shaped data (document, sentence, paragraph) will lead to positive, negative, or neutral trait. This research used document text about Indonesian movie review which was obtained from Twitter. The method used in this research was Naïve Bayes using Ensemble Features instead of only using Bag of Words Features. There are several types of features were used for this ensemble i.e. Twitter specific features, textual features, part of speech features, and lexicon-based features, and Bag of Words. Experiment Results showed that system f-measure value using Ensemble Features is 0.88. Meanwhile, Bag of Words Features has better performance with 0.94 f-measure value. © 2018 IEEE.

Affiliations

Faculty of Computer Science, Brawijaya University, Malang, Indonesia; Sekolah Menengah Atas Negeri 6 Balikpapan, Balikpapan, Indonesia