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Book ChapterDOI

Tourists visit and photo sharing behavior analysis: a case study of Hong Kong temples

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.

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Citations
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Journal ArticleDOI

A Tourist Flow Prediction Model for Scenic Areas Based on Particle Swarm Optimization of Neural Network

Nan Chen, +1 more
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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Proceedings ArticleDOI

Mapping the world's photos

TL;DR: This work uses the spatial distribution of where people take photos to define a relational structure between the photos that are taken at popular places, and finds that visual and temporal features improve the ability to estimate the location of a photo, compared to using just textual features.
Journal ArticleDOI

Modeling Tourist Movements: A Local Destination Analysis

TL;DR: In this paper, the authors developed models depicting the spatial movement patterns of tourists within a destination using an inductive approach based on urban transportation modeling and tourist behavior, to identify explanatory factors that could influence movements.
Journal ArticleDOI

Asymmetric effects of online consumer reviews

TL;DR: In this article, the authors assess the effect of review ratings on usefulness and enjoyment and find that people perceive extreme ratings (positive or negative) as more useful and enjoyable than moderate ratings, giving rise to a U-shaped line with asymmetric effects.
Journal ArticleDOI

Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos

TL;DR: In this paper, the authors present a new approach to this task by exploiting the socially generated and user-contributed geotagged photos now made publicly available on the Internet, focusing on Hong Kong inbound tourism using 29,443 photos collected from 2100 tourists.
Proceedings ArticleDOI

Generating summaries and visualization for large collections of geo-referenced photographs

TL;DR: A framework for automatically selecting a summary set of photos from a large collection of geo-referenced photographs, based on spa-tial patterns in photo sets, as well as textual-topical patterns and user (photographer) identity cues, which can be expanded to support social, temporal, and other factors.
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The results indicate four popular temples that attracted most tourists taking photos.