Unpacking the Emotions behind TripAdvisor Travel Reviews: The Case Study of Gatlinburg, Tennessee

ABSTRACT

This study investigated how tourists’ emotions about their travel experiences were presented through TripAdvisor travel reviews targeting Gatlinburg, Tennessee due to its historical and geographical importance as a tourist destination. After selecting five Gatlinburg tourist attractions based on their review quantity, we conducted a polarity analysis of each tourist attraction and performed sentiment analyses based on the classical emotion criteria of psychology (i.e., six basic emotions – anger, disgust, fear, joy, sadness, and surprise). The findings revealed that visitors tended to have favorable emotional responses toward the five attractions, and the results of polarity and sentiment analyses of respective attractions corresponded to their TripAdvisor ratings.

KEYWORDS:

• Tourist emotions
• sentiment analysis
• text mining
• TripAdvisor travel reviews
• tourism destination
• Gatlinburg

Notes

1. Based on the Bayes’ Theorem, Naïve Bayes classifier trains data to learn the probability of class membership and assumes that the features are conditionally independent in each class. With new data, the joint probabilities of predictors assign each category to the most likely class membership (Chapman & Feit, 2015).

2. Tourist attractions at a given destination include establishments for sightseeing, entertainment, or education (Weidenfeld et al., 2014).