From Footprint to Friendship

Abstract

In this paper we aim at addressing the correlation between two critical factors in mobile social networks (MSNs): the social-relationship networking among users and the spatial mobility pattern of users. Specifically, we investigate the impact of users' spatial distribution on their social relationship formation in MSNs. Based on the geolocation data (check-in records) and social relation data of MSN users, we propose a model, called neighborhood-cardinality-based model (NCBM), to describe this impact by taking into account both the multiple home-points/hotspots property of spatial mobility and the long-tailed social relationship degree distribution of MSN users. We define a fundamental quantity for each user, i.e., the so-called neighborhood cardinality, to measure how many and how often other MSN users visit his nearby area with a given range. The core of NCBM is a principle: The probability that a user, say u, is followed by another user, say v, obeys a power law distribution of the neighborhood cardinality of user u. The proposed formation model is evaluated on two large check-in datasets: Brightkite and Gowalla. Our experimental results indicate that the proposed formation model provides a useful paradigm for capturing the correlation between MSN users' mobility patterns and social relationships.