Exploring Temporal Egocentric Networks in Mobile Call Graphs

The structure of customer communication network provides us the insights into the function of customers´ relationships. In this paper, we use egocentric social network to explore how people manage their personal and group communications over time. Our primary goal is that our findings can provide business insights and help devise strategies for telecom service providers. We are interested in tracking changes in large-scale mobile networks and examining the evolution processes of customer egocentric networks. By defining several statistical metrics, we can investigate the egocentric networks´ evolution trends and their communication patterns. We explore several temporal real-world mobile call graphs and find an interesting phenomenon in these temporal networks which is the neighboring vertices´ egocentric networks have assortiative evolution trends. By taking a visual analytics approach, we track the changes in the customer egocentric networks and explore some highly correlated customers´ egocentric networks visually. We detect several interesting communication patterns by visualizing the egocentric networks which may give us more hints on customers´ communication trends in their egocentric networks.