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Using Geotagged Facial Expressions to Visualize and Characterize Different Demographic Groups' Emotion in Theme Parks

Overview
Journal Sci Rep
Specialty Science
Date 2024 Sep 9
PMID 39251641
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Abstract

Tourism is an emotional sphere, and researchers focus on emotions to optimize tourism experiences. Tourism studies on emotions mostly ignore differences in emotions across demographic tourist groups by gender and age, thus limiting the understanding of emotions to the explicit characteristics of tourists' emotions. On the basis of geotagged facial expressions on social media platforms, this study aims to visualize the emotions of groups in scenic spots and then reveal the variations between groups' emotions within theme parks. By employing a facial recognition algorithm, an emotion distribution graph was proposed to represent groups' emotions in detail. Some analytical methods were combined to characterize of the emotion distribution of each group. Through a comprehensive comparison, the results suggest that there are unique characteristics of emotion distribution for each group and considerable variations between them. This study helps researchers achieve a deeper understanding of tourists' emotional differences and enhances the theorization of emotions. This research also highlights the advantages and significant practical implications of our method framework.

References
1.
Russell J . Is there universal recognition of emotion from facial expression? A review of the cross-cultural studies. Psychol Bull. 1994; 115(1):102-41. DOI: 10.1037/0033-2909.115.1.102. View

2.
Matsuda Y, Fedotov D, Takahashi Y, Arakawa Y, Yasumoto K, Minker W . EmoTour: Estimating Emotion and Satisfaction of Users Based on Behavioral Cues and Audiovisual Data. Sensors (Basel). 2018; 18(11). PMC: 6263657. DOI: 10.3390/s18113978. View

3.
Scherer K, Moors A . The Emotion Process: Event Appraisal and Component Differentiation. Annu Rev Psychol. 2018; 70:719-745. DOI: 10.1146/annurev-psych-122216-011854. View

4.
Carvache-Franco O, Carvache-Franco M, Carvache-Franco W, Iturralde K . Topic and sentiment analysis of crisis communications about the COVID-19 pandemic in Twitter's tourism hashtags. Tour Hosp Res. 2023; 23(1):44-59. PMC: 9014346. DOI: 10.1177/14673584221085470. View

5.
Mauss I, Robinson M . Measures of emotion: A review. Cogn Emot. 2009; 23(2):209-237. PMC: 2756702. DOI: 10.1080/02699930802204677. View