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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Bibliographic Details
Published in:Journal of travel & tourism marketing Vol. 42; no. 5; pp. 693 - 707
Main Authors: Luo, Yi, Zheng, Jie, Tang, Liang Rebecca, Wang, Xi, Yang, Lei
Format: Journal Article
Language:English
Published: Binghamton Routledge 13.06.2025
Taylor & Francis LLC
Subjects:
Coding theory
Deep learning
Dual-coding theory
image classification
online review
twitter
ISSN:1054-8408, 1540-7306
Online Access:Get full text
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Summary: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.
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ISSN:1054-8408
1540-7306
DOI:10.1080/10548408.2025.2455436