Determining tourist satisfaction from travel reviews

Shuang Song (), Hidenori Kawamura (), Junichi Uchida () and Hajime Saito ()
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Shuang Song: Hokkaido University
Hidenori Kawamura: Hokkaido University
Junichi Uchida: Otaru University of Commerce
Hajime Saito: Hokkaido Information University

Information Technology & Tourism, 2019, vol. 21, issue 3, No 3, 337-367

Abstract: Abstract This study employed text data mining to demonstrate the reliability of identifying tourist needs from travel reviews by comparing the results of a traditional tourism survey with the attitudes expressed in travel reviews. In this study, we focused our analysis on tourist satisfaction and adopt the results of a governmental satisfaction survey implemented in Hokkaido, Japan (n = 1709) for referential statistics. We used manual techniques to extract attitudes from 1058 samples of reviews (in English, Simplified Chinese, and Traditional Chinese) posted on TripAdvisor by tourists from seven different regions. By calculating the Pearson’s r, we found a (strong) positive correlation between attitudes in reviews and the satisfaction rates recorded in the guest survey in six out of seven regions (p

Keywords: Text mining; Needs investigation; Cross language; Pearson correlation coefficient (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s40558-019-00144-3

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