Temporal analysis of telecom call graphs

Real world graphs like call graphs, email communication graphs are temporal in nature in which edges between nodes exist only for a limited span of time. Temporal analysis can lead to new insights such as densification laws and shrinking diameters. In this paper we have analyzed temporal properties like diameter, clustering coefficient, number of calls and other properties of Call Detail Records of more than 1 billion calls. To analyze the data we used moving windows at multiple time scales, such as day-night windows, weekday-weekend windows, etc. We also analyzed the number of unique calls with respect to days of week which lead to the rather surprising conclusion that no day of week dominates other days in terms of highest number of unique calls. To best of our knowledge, this is the first study of temporal properties on telecom call graphs with this particular set of splits.