Do you "like" my tweets? Exploring verbal and visual cues in traveler's dual-coding process

Grounded in the dual-coding theory, this study explores the nuanced factors influencing individuals' travel intentions during the COVID-19 crisis. Utilizing sophisticated text mining and deep learning techniques on a corpus of travel-related tweets, three verbal cues (nature, humanities, touris...

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Veröffentlicht in:Journal of travel & tourism marketing Jg. 42; H. 5; S. 693 - 707
Hauptverfasser: Luo, Yi, Zheng, Jie, Tang, Liang Rebecca, Wang, Xi, Yang, Lei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Binghamton Routledge 13.06.2025
Taylor & Francis LLC
Schlagworte:
Coding theory
Deep learning
Dual-coding theory
image classification
online review
twitter
ISSN:1054-8408, 1540-7306
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Zusammenfassung:Grounded in the dual-coding theory, this study explores the nuanced factors influencing individuals' travel intentions during the COVID-19 crisis. Utilizing sophisticated text mining and deep learning techniques on a corpus of travel-related tweets, three verbal cues (nature, humanities, tourism services), and five visual cues (foods, people, scenery, pandemic control, promotion) were identified. Findings reveal that most visual cues, such as food, people, and pandemic control, positively impact the appeal of travel tweets, while promotion has a negative effect. Among the verbal cues, nature and humanities contribute positively to likes, whereas tourism services show a negative influence.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:1054-8408
1540-7306
DOI:10.1080/10548408.2025.2455436