A Sentiment-Based Model for Credible Online Reviews

• Main Authors: Yi-Pei Chen, 陳怡蓓
• Other Authors: 張瑋倫
• Format: Others
• Language: zh-TW
• Published: 2015
• Online Access: http://ndltd.ncl.edu.tw/handle/d5q3km

碩士 === 淡江大學 === 企業管理學系碩士班 === 103 === A survey from 1111 Job Bank (Taiwan) in 2014 shows around 97% participants read online reviews and rankings regarding travel information. Online reviews and word-of-mouth are extremely important to consumers. However, online reviews are complex nowadays and users need to spend much time on reading from various sources. In addition, online platform like TripAdvisor only uses five levels for reviewers which lack credibility. 67％ of users read no more six reviews before consumption. As a result, this research attempts to discover key factors that affect customer decision making. We propose a model by using sentiment analysis in terms of positive and negative words and the concept of credibility inferred from Prospect Theory. We assume all users are neutral in reading the reviews (no fixed reference point). That is, higher reliable reviews may have lower risk, and vice versa. This research uses TripAdvisor to examine the proposed model and selects 10 out of 271 hotels in Las Vegas from Jan. to Feb. in 2015. This is also the peak season for traveling in Las Vegas. We discovered the overall ranking decreased of 10 hotels through sentiment analysis. However, only Skylofts at MGM Grand reduce 1 level. The rest of 9 hotels reduced 2 or more levels after considering the factor of credibility. Moreover, the factor of credibility affected overall ranking. The ranking of Four Season Hotel increased from 6 to 1. The ranking of Staybridge Suites Hotel decreased from 1 to 9. Apparently, the factor of credibility has greater influence on hotels’ ranking than sentiment analysis. This research discovers negative emotion and low credibility reviews have more influence on the hotels’ ranking. In this research, we combine sentiment analysis with credibility in the proposed model and provide more clues to enterprises on operation, management, and strategic decisions.