[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.13160/ricns.2021.14.2.35

Modeling Topic Extraction-based Sentiment Analysis Based on User Reviews

Kim, Tae-Yeun (National Program of Excellence in Software center, Chosun University)

Publication Information

Journal of Integrative Natural Science / v.14, no.2, 2021 , pp. 35-40 More about this Journal

Abstract

In this paper, we proposed a multi-subject-level sentiment analysis model for user reviews using the Latent Dirichlet Allocation (LDA) method targeting user-generated content (UGC). Data were collected from users' online reviews of hotels in major tourist cities in the world, and 30 hotel-related topics were extracted using the entire user reviews through the LDA technique. Six major hotel-related themes (Cleanliness, Location, Rooms, Service, Sleep Quality, and Value) were selected from the extracted themes, and emotions were evaluated for sentences corresponding to six themes in each user review in the proposed sentiment analysis model. Sentiment was analyzed using a dictionary. In addition, the performance of the proposed sentiment analysis model was evaluated by comparing the emotional values for each subject in the user reviews and the detailed scores evaluated by the user directly for each hotel attribute. As a result of analyzing the values of accuracy and recall of the proposed sentiment analysis model, it was analyzed that the efficiency was high.

Keywords

LDI; user-generated content;

Citations & Related Records

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