Book ChapterDOI
Tourists visit and photo sharing behavior analysis: a case study of Hong Kong temples
Rosanna Leung,Huy Quan Vu,Jia Rong,Yuan Miao +3 more
- pp 197-209
TLDR
A study of extracting geotagged photos uploaded by tourists to one of the popular social media sites, Flickr, for tourists’ visit and sharing behavior analysis of Hong Kong temples, which indicates four popular temples that attracted most tourists taking photos.Abstract:
Travel statistics report published by the tourism board was one of the important sources that attraction managers used to plan for marketing strategies. However, only a limited number of famous attractions were involved in such reports, therefore rare information was gathered for 2nd or 3rd tier attractions, such as temples. These small attractions were kept away from many tourists’ knowledge or travel plan so that it is also a difficulty to explore their visit behaviors. Fortunately, social media sites have been rapidly developed and widely used in our lives, to fill this blank with a large number of active users, who shared their travel experiences by writing textual comments and uploading travel photos. This provides scholars and managers with opportunities to understand tourists’ behaviors and the potential attractions they are interested in, by analyzing the photos they uploaded and shared online. In this paper, we report a study of extracting geotagged photos uploaded by tourists to one of the popular social media sites, Flickr, for tourists’ visit and sharing behavior analysis of Hong Kong temples. The results indicate four popular temples that attracted most tourists taking photos. The behavior analysis shows the difference preferences of tourists from various locations and the trend changes of their visits in the past 5 years.read more
Citations
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Journal ArticleDOI
A Tourist Flow Prediction Model for Scenic Areas Based on Particle Swarm Optimization of Neural Network
TL;DR: Experimental results show that the proposed model can effectively predict the tourist flow in scenic areas, and provide a desirable prediction tool for other fields.
Exploring Tourism Activities of Tourists and Residents through Convolutional Neural Network-based SNS Photo Classification
TL;DR: This study aims to analyze the characteristics of tourists and residents’ tourism activities by analyzing photos posted on Flickr, a photo-sharing SNS.
Proceedings ArticleDOI
Destination Choice Through Social Media by Domestic Tourists in Indonesia
TL;DR: In this paper , the authors investigate which aspects of social media significantly affect tourists' destination choice and find that photo attractiveness and trustworthiness of content have significant relationships while textual information did not have a significant relationship with the effect of Instagram on destination choice.
Proceedings ArticleDOI
Propagation measure on circulation graphs for tourism behavior analysis
TL;DR: The propagation effect of tourists on the territory thanks to geotagged circulation graphs is studied, and a new weighted measure is introduced for circulation characterization based on both topologies and distances.
References
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