This study aims to analyze user-generated travel photos (UGTPs) to decode tourists’ motivations for traveling abroad. To the best of the authors’ knowledge, this research is the first attempt to analyze and quantitatively compare UGTPs taken in foreign versus domestic-equivalent destinations.
Data were collected from Weibo from 2022 to 2024. Using DeepSentiBank, the authors’ analyzed 1,000 photos from major foreign (Phuket) and domestic (Sanya) coastal destinations for Chinese tourists. The extracted visual data was then mapped to push–pull factors using natural language processing, and the results were compared with inferential statistics.
The findings revealed similarities in coastal destination pull factors. “Beach” and “View” were statistically exhibited in the uploaded photos. Interestingly, different from domestic trips, UGTPs taken on foreign trips highlighted tourists’ tendencies toward exciting experiences and outdoor tones.
This research contributes to the tourism literature in three ways. First, it is the first to link elements identified in UGTPs with travel motivation theory. Second, it confirms the adventurous nature of foreign trips through the lens of tourists’ cameras. Third, it underscores the importance of beaches, views and food as the main pull factors for coastal destinations, regardless of whether the trip is foreign or domestic.
