The analysis and modeling of large and complex real-world networks has become indispensable across the diverse set of social, technological, and natural worlds. While the field remains heterogeneous and diverse, we have seen emerging signs of convergence. There has been growing computer science and statistical literature expounding on topics of analyzing and visualizing time-varying networks, a subject popularized earlier within the physics community. Social media researchers are beginning to use problem-specific structure to infer between social influence, homophile, and external forces -- areas historically of intense interest amongst statisticians and social scientists. Highly complex application domains, such as brain and financial networks, are coming into the scope of the field.
The primary goal of the workshop is to actively promote a concerted effort to address theoretical, methodological and computational issues that arise when modeling and analyzing dynamic networks, stochastic processes on networks, and collection of interactions. To this end, we aim at bringing together researchers from applied disciplines such as sociology, economics, medicine and biology, together with researchers from more theoretical disciplines such as mathematics, statistics, physics and computer science. All these communities have a long-standing interest in modeling large scale networks, and we would like to foster cross-disciplinary collaborations and exchanges in order to identify directions that can provide theoretical and computational foundations to push forward this extremely important field.
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