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Traveller-generated destination image: Analysing Flickr photos of 193 countries worldwide

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dc.contributor.authorViriya Taecharungrojen_US
dc.contributor.authorBoonyanit Mathayomchanen_US
dc.contributor.otherMahidol Universityen_US
dc.date.accessioned2020-11-18T08:29:46Z
dc.date.available2020-11-18T08:29:46Z
dc.date.issued2020-01-01en_US
dc.description.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.en_US
dc.identifier.citationInternational Journal of Tourism Research. (2020)en_US
dc.identifier.doi10.1002/jtr.2415en_US
dc.identifier.issn15221970en_US
dc.identifier.issn10992340en_US
dc.identifier.other2-s2.0-85091732383en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/59911
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091732383&origin=inwarden_US
dc.subjectBusiness, Management and Accountingen_US
dc.subjectEnvironmental Scienceen_US
dc.subjectSocial Sciencesen_US
dc.titleTraveller-generated destination image: Analysing Flickr photos of 193 countries worldwideen_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091732383&origin=inwarden_US

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