A big data framework to identify tourist interests based on geotagged travel photos

Lina Zhong, Liyu Yang, Jia Rong, Haoyu Kong

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Understanding the interests of tourists is a key skill for attraction managers to prepare plans and make strategic decisions in tourism marketing. The rapid growth and spread of social media websites provide an information-rich channel from which tourism researchers and managers can collect a large amount of text-based reviews or comments and photos relating to the past travel experiences of users. The travel photos with geographic information are especially helpful in identifying the geographical location of the destinations. By analyzing these big data in various formats can help to understand the interests of tourists at destinations. In this paper, a framework is proposed to identify the interests of tourists by integrating information carried by the geotagged photos shared on social media websites. Such an approach is expected to provide sustainable tracking on popular places of interest (POIs) updated by tourists and pick the best representative photos taken by them. The performance of this model is evaluated by conducting a case study using the geotagged photos taken in Hong Kong. A case study proved this proposed framework could make a thriving tourism industry more efficient.

Original languageEnglish
Pages (from-to)85294-85308
Number of pages15
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 28 Apr 2020

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