Towards a Sentiment Analysis Model Based on Semantic Relation Analysis

Thien Khai Tran and Tuoi Thi Phan
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Thien Khai Tran: Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology - VNU-HCM, Hồ Chí Minh, Vietnam & Faculty of Information Technology, Ho Chi Minh City University of Foreign Languages and Information Technology, Hồ Chí Minh, Vietnam
Tuoi Thi Phan: Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology - VNU-HCM, Hồ Chí Minh, Vietnam

International Journal of Synthetic Emotions (IJSE), 2018, vol. 9, issue 2, 54-75

Abstract: Sentiment analysis is an important new field of research that has attracted the attention not only of researchers, but also businesses and organizations. In this article, the authors propose an effective model for aspect-based sentiment analysis for Vietnamese. First, sentiment dictionaries and syntactic dependency rules were combined to extract reliable word pairs (sentiment - aspect). They then relied on ontology to group these aspects and determine the sentiment polarity of each. They introduce two novel approaches in this work: 1) in order to “smooth” the sentiment scaling (rather than using discrete categories of 1, 0, and -1) for fined-grained classification, then extract multi-word sentiment phrases instead of sentiment words, and 2) the focus is not only on adjectives but also nouns and verbs. Initial evaluations of the system using real reviews show promising results.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jse000:v:9:y:2018:i:2:p:54-75

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