Effective Modeling and Analysis in Computational Social Systems

Understanding and analyzing how human beings respond, adapt, and react is a major scientific endeavor. Human beings are inherently complex and how we behave and interact is not easily modeled or quantified. This talk focuses on computational social systems; specifically on how to systematically represent socio-cultural factors, their infusion into computational models and simulations, a new paradigm for designing and analyzing the efficiency and efficacy of methodologies dealing with dynamic information, and application to real-world scenarios. Specifically we will present a framework which can infuse various forms of information within computational representations that allow for incomplete knowledge which leads to more effective and meaningful social networks analyses. We refer to such new network structures as Culturally-Infused Social Networks (CISN). We will also present methods for social networks analyses that deal with dynamically changing information. We focus on how fundamental tools and techniques can be represented mathematically such that they can be decomposed to produce critical computational savings without loss of information. These methods, which we refer to as anytime anywhere methodologies, also produce partial results that can be used for “re-use” in computation; thus providing a means to account for differences or changes in structure. Theoretical analysis and experimental validation of results are provided to compare and show overall utility of approach.