FROM METADATA TO POLICY: USING PHOTO-SHARING PLATFORMS TO UNDERSTAND TOURISM DYNAMICS
Abstract
Social networking platforms and websites designed for photo sharing provide access to images of various locations. Several of these services additionally include geo-tagged metadata, indicating the precise geographical coordinates where the photographs were taken. When aggregated in substantial quantities, such data can serve as a proxy for identifying visitor interests, revealing which sites attract tourist attention and how these locations are perceived by other users. Consequently, the analysis of metadata derived from photographs posted on diverse online platforms enables the examination of tourist preferences, their movement patterns within a destination, and the evaluations expressed by other users regarding the shared images. This study undertakes an analysis of a statistically significant dataset of photographs uploaded by contributors to Google Local Guides, a component of the Google Maps platform. The city of Ohrid, is employed as the case study. The findings of this research are expected to provide valuable insights both for prospective visitors and for policymakers.
Downloads
References
Bhatt, P., & Pickering, C. M. (2022). Destination image of Chitwan National Park, Nepal: Insights from a content analysis of online photographs. Journal of Outdoor Recreation and Tourism, 37, 100488.
Chen, W., Xu, Z., Zheng, B., & Luo, C. (2019). Geo-Tagged Photo Metadata Processing Method for Beijing Inbound Tourism Flow. ISPRS International Journal of Geo-Information, 8(12), 556.
García Palomares, J. C., Gutiérrez, J., & Mínguez, C. (2015). Identification of tourist hot spots based on social networks: A comparative analysis of European metropolises using photo sharing services and GIS. Applied Geography, 63, 408–418.
Giglio, S., Bertacchini, F., Bilotta, E., & Pantano, P. (2019). Using social media to identify tourism attractiveness in six Italian cities. Tourism Management, 72, 306–312.
Kádár, B. (2014). Measuring tourist activities in cities using geotagged photography. Tourism Geographies, 16(1), 88–104.
Lee, C., Richardson, S., Goh, E., & Presbury, R. (2023). From the tourist gaze to a shared gaze: Exploring motivations for online photo sharing in present day tourism experience. Tourism Management Perspectives, 46, 101099.
Li, H., Zhang, L., & Hsu, C. H. C. (2023). Research on user‑generated photos in tourism and hospitality: A systematic review and way forward. Tourism Management, 96, 104714.
Önder, I., Koerbitz, W., & Hubmann‑Haidvogel, A. (2016). Tracing tourists by their digital footprints: The case of Austria. Journal of Travel Research, 55(5), 566–573.
Örücü, Ö. K., Arslan, E. S., Kaymaz, I., Hoşgör, E., & Tekin Cüre, C. (2024). Modeling cultural ecosystem services using social media photos: The case of Denizli, Türkiye. Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi, 21(2), 205–212.
Senarathne, M. P., Hewakuruppu, D. T., Perera, P., Silva, R. M., & Wickramaarachchi, D. C. (2024). Exploring tourist flow patterns through geotagged social media data: A case study from Sri Lanka. In Proceedings of the International Forestry and Environment Symposium, 28,
Valls, F., & Roca, J. (2021). Visualizing digital traces for sustainable urban management: Mapping tourism activity on the virtual public space. Sustainability, 13(6), 3159.
Walden‑Schreiner, C., Rossi, S. D., Barros, A., Pickering, C., & Leung, Y. Fai (2018). Using crowd‑sourced photos to assess seasonal patterns of visitor use in mountain‑protected areas. Ambio, 47, 781–793.
Wicaksono, A., Farda, N. M., Khakhim, N., & Wibowo, T. W. (2023). Flickr photos analysis for beach tourism management in Bantul Regency, Indonesia: Popularity and tourist attractions. Forum Geografi, 35(1).
Leung, R., Quan, H., & Rong, J. (2017). Understanding tourists’ photo sharing and visit pattern at non‑first tier attractions via geotagged photos. Information Technology & Tourism, 17(1), 55–74.
Zhang, K., Chen, Y., & Lin, Z. (2020). Mapping destination images and behavioral patterns from user‑generated photos: A computer vision approach. Asia Pacific Journal of Tourism Research, 25(11), 1199–1214.b
