Abstract

Humans are social animals, they interact with different com-munities of friends to conduct different activities. The lit-erature shows that human mobility is constrained by their social relations. In this paper, we investigate the social im-pact of a person’s communities on his mobility, instead of all friends from his online social networks. This study can be particularly useful, as certain social behaviors are influ-enced by specific communities but not all friends. To achieve our goal, we first develop a measure to characterize a per-son’s social diversity, which we term ‘community entropy’. Through analysis of two real-life datasets, we demonstrate that a person’s mobility is influenced only by a small frac-tion of his communities and the influence depends on the social contexts of the communities. We then exploit ma-chine learning techniques to predict users ’ future movement based on their communities ’ information. Extensive experi-ments demonstrate the prediction’s effectiveness.