Emotion Detection and Recognition from Vietnamese Text
Phan Thi Ha1, Phuong Nguyen2

1Dr. Phan Thi Ha, Department of Information Technology, Posts and Telecommunications Institude of Technology, Hanoi Vietnam.
2Dr. Phuong Nguyen, Department of Information Technology, Posts and Telecommunications Institude of Technology, Hanoi Vietnam.
Manuscript received on 15 April 2017 | Revised Manuscript received on 22 April 2017 | Manuscript Published on 30 April 2017 | PP: 9-13 | Volume-6 Issue-9, April 2017 | Retrieval Number: I2426046917/17©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The areas of Emotion Detection and Recognition from text have become increasingly interested in finding and exploiting information about people. Various problems have been identified such as product evaluations, emotional recognition and emotional findings in the text. In this paper, we present the application of Support Vector Machine (SVM) to detect emotional states in the Vietnamese sentences. The results of our experiments on datasets extracted from Vietnamese novels show that our proposed SVM classification method has higher accuracy than unsupervised learning methods.
Keywords: Emotion Detection, Emotion Classification, Emotions, Natural Language Processing, Learning Support Vector Machine.

Scope of the Article: Pattern Recognition