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Characterizing International Travel Behavior from Geotagged Photos: A Case Study of Flickr

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  • Yihong Yuan
  • Monica Medel

Abstract

Recent advances in multimedia and mobile technologies have facilitated large volumes of travel photos to be created and shared online. Although previous studies have utilized geotagged photos to model travel patterns at individual locations, there is limited research on how these datasets can model international travel behavior and inter-country travel flows—a crucial indicator to quantify the interactions between countries in tourism economics. Realizing the necessity to investigate the potential of geotagged photos in tourism geography, this research investigates international travel patterns from two perspectives: 1) We apply a series of indicators (radius of gyration (ROG), number of countries visited, and entropy) to measure the descriptive characteristics of international travel in different countries; 2) By constructing a gravity model of trade, we investigate how distance decay influences the magnitude of international travel flow between geographic entities, and whether (or how much) the popularity of a given destination (defined as the percentage of tourist income in national gross domestic product (GDP)) affects travel choices in different countries. The results provide valuable input to various commercial applications such as individual travel planning and destination suggestions.

Suggested Citation

  • Yihong Yuan & Monica Medel, 2016. "Characterizing International Travel Behavior from Geotagged Photos: A Case Study of Flickr," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-18, May.
    • Handle: RePEc:plo:pone00:0154885
    DOI: 10.1371/journal.pone.0154885
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    References listed on IDEAS

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    2. Xingshan Wang & Lu Tang & Wei Chen & Jianxin Zhang, 2022. "Impact and Recovery of Coastal Tourism Amid COVID-19: Tourism Flow Networks in Indonesia," Sustainability, MDPI, vol. 14(20), pages 1-17, October.

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