document: A framework for analysis of dynamic social networks Finding patterns of social interaction within a population has wide-ranging applications including : disease modeling , cultural and information transmission , and behavioral ecology . Social interactions are often modeled with networks . A key characteristic of social interactions is their continual change . However , most past analyses of social networks are essentially static in that all information about the time that social interactions take place is discarded . In this paper , we propose a new mathematical and computational framework that enables analysis of dynamic social networks and that explicitly makes use of information about when social interactions occur .
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