Journal
INTERNATIONAL JOURNAL OF TOURISM RESEARCH
Volume 23, Issue 3, Pages 417-441Publisher
WILEY
DOI: 10.1002/jtr.2415
Keywords
destination image; Flickr; Google Cloud Vision AI; image analysis; latent Dirichlet allocation
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This research introduces a method that combines Google Cloud Vision AI and latent Dirichlet allocation to identify common destination images and compare destinations worldwide, providing a more effective way for Destination Marketing Organizations to analyze and promote destinations.
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.
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