4.4 Article

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

Journal

INTERNATIONAL JOURNAL OF TOURISM RESEARCH
Volume 23, Issue 3, Pages 417-441

Publisher

WILEY
DOI: 10.1002/jtr.2415

Keywords

destination image; Flickr; Google Cloud Vision AI; image analysis; latent Dirichlet allocation

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available