Detecting Emotions in User Generated Content and Their Influence on Tourist Satisfaction

Tobias Eberle (), Matthias Fuchs and Wolfram Höpken
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Tobias Eberle: Mid-Sweden University
Matthias Fuchs: Libera Università Di Bolzano
Wolfram Höpken: Ravensburg-Weingarten University of Applied Sciences

A chapter in Information and Communication Technologies in Tourism 2025, 2025, pp 201-211 from Springer

Abstract: Abstract In today’s society, online reviews play a significant role in tourist’s decision making and understanding the emotions expressed in reviews can provide valuable insights into tourists’ perceptions. The study bears an understanding of emotions that tourists express in user generated content, aiming to gain insights into the satisfaction experienced within touristic activities. In contrast to traditional research, this study conceptualizes emotions not only in terms of positive, negative, or neutral sentiment, but builds on emotion theory which proposes primary emotions, such as joy, love, anger, or fear. The study successfully shows that primary emotions in online reviews can be detected using deep learning methods. Findings reveal the multi-faceted nature of emotional experiences within the scope of tourism and show the influence of certain emotions towards tourist satisfaction.

Keywords: Emotion detection; User generated content; Customer satisfaction; Deep learning; BERT (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-83705-0_17

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DOI: 10.1007/978-3-031-83705-0_17

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