Tourist Tour Planning Supported by Social Network Analysis

Abstract

In line with the just recent "social machines" phenomena, this work proposes an extension based on social network analysis (SNA) to the tourist tour planning. It is able to estimate the tourist's satisfaction with individual Point of Interest (POI), and accordingly recommend or not that POI in the tour in view for that tourist. We first provide a model of developing a social network comprised of tourists and reviewers including their personal attributes (like age or gender in their social profile), preferences of reviewers for certain POIs, and tourists' preferences for certain types or categories of POIs (say archeology) in a given touristic destination. Then in the second part, an algorithm for grouping into "islands" of most similar reviewers to a certain tourist is defined. Additionally, a ranking algorithm based on authority centrality is adopted to identify the highest ranked reviewer within the island and recommend his preferred POI to a given tourist. The results of the evaluation tests prove our approach as feasible in estimating the tourist's satisfaction with individual POIs. Moreover, it is already promising since acting within a social network as opposed to its counterparts of less appreciation for the social dimension of user.