Investigating Online Destination Images Using a Topic-Based Sentiment Analysis Approach

Gang Ren and Taeho Hong
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Gang Ren: College of Business Administration, Pusan National University, Busan 46241, Korea
Taeho Hong: College of Business Administration, Pusan National University, Busan 46241, Korea

Sustainability, 2017, vol. 9, issue 10, 1-18

Abstract: With the development of Web 2.0, many studies have tried to analyze tourist behavior utilizing user-generated contents. The primary purpose of this study is to propose a topic-based sentiment analysis approach, including a polarity classification and an emotion classification. We use the Latent Dirichlet Allocation model to extract topics from online travel review data and analyze the sentiments and emotions for each topic with our proposed approach. The top frequent words are extracted for each topic from online reviews on Ctrip.com . By comparing the relative importance of each topic, we conclude that many tourists prefer to provide “suggestion” reviews. In particular, we propose a new approach to classify the emotions of online reviews at the topic level utilizing an emotion lexicon, focusing on specific emotions to analyze customer complaints. The results reveal that attraction “management” obtains most complaints. These findings may provide useful insights for the development of attractions and the measurement of online destination image. Our proposed method can be used to analyze reviews from many online platforms and domains.

Keywords: user-generated content; online destination image; latent Dirichlet allocation; tourist attraction; topic-based sentiment analysis; emotion classification (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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