Abstract

Abstract Social media plays an important role in tourism industry, especially for individual travel planning and tourism entities preparing business plans. Only a limited number of first-tier attractions were reported in tourism bureau’s travel statistics documents, which cannot satisfy the needs of non-first tier attraction managers preparing their marketing strategies. With the rich tourists reviews and photos publicly available on social network platform, researchers and attraction manager could analyzing these geotagged photos to find out the potentials of the attractions including tourists interests and their travel pattern. In this study, we report our work on extracting and processing of geotagged photos uploaded by inbound tourists on Flickr.com to study tourists’ photo sharing and visiting pattern during their visits at Hong Kong temples. Four popular temples were identified automatically using P-DBSCAN density clustering from geotagged tourists photos. The travel pattern analysis had shown that tourists from different country of residence have different temple choice. Particularly, a closer look at the repeated tourists in the past five years, and special focus on photo uploading habits are discussed in our findings.

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