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Evy Kamilah Ratnasari
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Computer Science & IT

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USER EMOTION IDENTIFICATION IN TWITTER USING SPECIFIC FEATURES: HASHTAG, EMOJI, EMOTICON, AND ADJECTIVE TERM Yuita Arum Sari; Evy Kamilah Ratnasari; Siti Mutrofin; Agus Zainal Arifin
Jurnal Ilmu Komputer dan Informasi Vol 7, No 1 (2014): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)
Publisher : Faculty of Computer Science - Universitas Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (271.587 KB) | DOI: 10.21609/jiki.v7i1.252

Abstract

Abstract Twitter is a social media application, which can give a sign for identifying user emotion. Identification of user emotion can be utilized in commercial domain, health, politic, and security problems. The problem of emotion identification in twit is the unstructured short text messages which lead the difficulty to figure out main features. In this paper, we propose a new framework for identifying the tendency of user emotions using specific features, i.e. hashtag, emoji, emoticon, and adjective term. Preprocessing is applied in the first phase, and then user emotions are identified by means of classification method using kNN. The proposed method can achieve good results, near ground truth, with accuracy of 92%.
Co-Authors Agus Zainal Arifin Siti Mutrofin Yuita Arum Sari