Opinion mining of hotel customer-generated contents in Chinese weblogs

Chaochang Chiu, Nan-Hsing Chiu, Re-Jiau Sung and Pei-Yu Hsieh

Current Issues in Tourism, 2015, vol. 18, issue 5, 477-495

Abstract: Customer-generated contents in weblogs provide tourism organisations with valuable market intelligence and ongoing market research opportunities. In this study, an opinion mining method based on feature-based sentiment classification is proposed to extract the online electronic word-of-mouth on weblogs in Taiwan. For opinion extraction, a supervised semantic orientation using the point-wise mutual information (SO_PMI) algorithm based on the extension of Turney's unsupervised SO_PMI algorithm is proposed to extract the opinion words. In addition, a heuristic n-phrase rule is proposed to find out customer opinions about hotel attributes, including hotel image, services, price/value, food and beverage, room, amenities, and location. The experimental results show that the proposed approach mixed with supervised SO_PMI algorithm and heuristic n-phrase rule can demonstrate its effectiveness with acceptable classification and forecasting performances. Furthermore, a perceptual map based on correspondence analysis visually presents opinions comparison to provide the insight of competitive positions.

Date: 2015
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DOI: 10.1080/13683500.2013.841656

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