Spatio-temporal mobility analysis for community detection in the mobile networks using CDR data

Building or detecting community association is a key attribute in understanding relationships in social networks and their behavior. By detecting groups, we can address many issues related to population displacement and intelligent transportation systems. In this paper, we are presenting a method based on analyzing and exploring spatio-temporal mobility patterns from call detail records of mobile users to discover communities. Our proposed approach relies on deriving the events' occurrence in a cells coverage in time and space to match and categorize the users based on their mobility patterns extracted from call detail records data. The final results are the outcome of real experiments that demonstrate interesting and encouraging findings by using mobility patterns as a means to detect communities.