Viriya TaecharungrojBoonyanit MathayomchanMahidol University2020-11-182020-11-182020-01-01International Journal of Tourism Research. (2020)15221970109923402-s2.0-85091732383https://repository.li.mahidol.ac.th/handle/20.500.14594/59911© 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.Mahidol UniversityBusiness, Management and AccountingEnvironmental ScienceSocial SciencesArticleSCOPUS10.1002/jtr.2415