Abstract
Social network analysis has become widespread in recent years, especially in digital tourism. Indeed, the vast amount of data that tourists produce during their travels represents an effective source for interpreting their behaviors (geographics, demographics, psychographics, movement patterns). Since the classic measures unfit to those kind of information, this article presents a new measure to determine tourist profiles thanks to the digital traces left on social networks. This measure is based on geographic, demographic and pattern’s behaviors of the tourists as the context and the content of their trips. The approach is simulated and evaluated experimentally with a hierarchical clustering on the traces left by tourists on TripAdvisor in the French capital Paris. Clusters found correspond to tourism segment determined by the Tourism Office of Paris.
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Djebali, S., Gabot, Q., Guerard, G. (2023). Hierarchical Clustering and Measure for Tourism Profiling. In: Li, B., Yue, L., Tao, C., Han, X., Calvanese, D., Amagasa, T. (eds) Web and Big Data. APWeb-WAIM 2022. Lecture Notes in Computer Science, vol 13422. Springer, Cham. https://doi.org/10.1007/978-3-031-25198-6_12
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