ITR: Study of Dynamically Evolving Social Groups in Communication Networks

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This project will develop novel methods for the statistical analysis of the evolution of social groups acting within a large social network via a communications network, such as the Internet. The basis for the analysis is a set of probabilitistic laws (micro-laws) that govern the individual behavior of actors, which largely determines the macro-evolution of the social groups. The parameters of the macro-evolution can be measured and then used to determine, via reverse engineering, the parameters of the micro-laws that fit the observed evolution. Understanding the evolution of social communities will help determine resource allocation strategies for enhancing the functioning of these communities. The methods developed in this research can be used to locate, within a large social network, social groups that try to hide their inner communications. Such a system can be instrumental in preventing terrorists' attacks similar to those on September 11, 2001. The proposed research will also open up novel educational opportunities at the home university related to social network analysis.