Publication: Traveller-generated destination image: Analysing Flickr photos of 193 countries worldwide
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Issued Date
2020-01-01
Resource Type
ISSN
15221970
10992340
10992340
DOI
Other identifier(s)
2-s2.0-85091732383
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Mahidol University
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SCOPUS
Bibliographic Citation
International Journal of Tourism Research. (2020)
Suggested Citation
Viriya Taecharungroj, Boonyanit Mathayomchan Traveller-generated destination image: Analysing Flickr photos of 193 countries worldwide. International Journal of Tourism Research. (2020). doi:10.1002/jtr.2415 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/59911
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Title
Traveller-generated destination image: Analysing Flickr photos of 193 countries worldwide
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Abstract
© 2020 John Wiley & Sons Ltd The purpose of this research is to introduce a method that utilises a combination of Google Cloud Vision AI's label detection and a topic-modelling algorithm, latent Dirichlet allocation, to identify common destination images and to compare destinations worldwide. The study analyses 283,912 photos of 193 countries from Flickr.com, and 16 cognitive image attributes (CIAs) are identified. Subsequent hotspot analyses indicate the exact locations of these CIAs in three sample countries: France, the US, and Thailand. Destination marketing organisations (DMOs) can use this method to more effectively analyse and promote destinations during and after the COVID-19 pandemic.