ITR: Study of Dynamically Evolving Social Groups in Communication Networks

该项目将开发新的方法，用于统计分析通过通信网络（如互联网）在大型社会网络中活动的社会群体的演变。这种分析的基础是一套概率规律（微观规律），它支配着行动者的个体行为，在很大程度上决定着社会群体的宏观演化。可以测量宏观演化的参数，然后通过逆向工程来确定与观测到的演化相适应的微观规律的参数。了解社会社区的演变将有助于确定资源分配策略，以增强这些社区的功能。在这项研究中开发的方法可以用来定位，在一个大的社会网络中，社会群体，试图隐藏他们的内心交流。这样一个系统可以在防止类似2001年9月11日的恐怖袭击方面发挥重要作用。建议的研究也将在国内大学开辟与社会网络分析相关的新的教育机会。

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.