Sequence and Network Mining of Touristic Routes Based on Flickr Geotagged Photos

Abstract

Information provided by geotagged photos allow us to know where and when people have been, supporting a better understanding about tourist’s movement patterns across a destination. The aim of this paper is to study tourists’ movement patterns during their staying in Porto through the analysis of geotagged photos in order to fulfill marketing segmentation in an innovative way. For that purpose, the SPADE algorithm was used to find sequence patterns of tourists paths based on the time and location of the photos collected. Then, the K-Mode clustering algorithm was applied to these sequences in order to find identical behaviors in terms of paths followed by tourists. At the same time, in order to understand the influence of the different attractions on tourists’ paths, we performed a Social Network Analysis of the touristic attractions (spots, museums, streets, monuments, etc.). Based on the time and location of the photos collected, along with personal information, it was possible to understand tourists’ frequent movements across the city and to identify market segments based on a hybrid strategy.