TraMSNET: A mobile social network application for tourism

Abstract

By enabling users to leverage online social networks with location data, Location-based Social Networks (LBSN) support the most diverse human activities, in particular, tourism. Different applications aim to aid tourists to better experience their travels by matching co-located users based on what they have in common. Doing this, users with little in common but with potential to help each other given the context and place do not get connected. In this paper we introduce traMSNet, a LBSN that implements a matching algorithm skills in a touristic location. The idea is validated with a user survey, asking potential users about their needs when looking for a travel partner. Moreover, we present a matching algorithm and evaluated it with real tourists. Our evaluation shows that considering complementarity when matching individuals is preferred by the user. Therefore, by only considering similarities important issues are left aside.