Grant: Discovery Grants Program - Individual

My research proposal brings together web-based dynamic social networks (WDSN) analysis and representational theory of measurement within category theory and Markov decision processes. WDSN differ from traditional social networks in that they are cellular, distributed, web-based thus larger, dynamic, and may contain varying levels of uncertainty. The long term goals of my research deal with the following issues: (1) how to best model WEB-based dynamic social network so that its essential properties, such as evolution laws, time progress, response strategies and self-healing are precisely captured in the model? (2) what are the measurement goals that need to be achieved throughout WDSN evolution? A set of candidate metrics for describing the WDSN goals have to be defined. Two kinds of uncertainties - measurement errors and goals' fuzziness, can be differentiated in the measurement data. How to assess their combined effect on the measurement process and to assess the plausible effects on subsequent decision-making rules? (3) what are the rules for measurement-based decision-making under risk of uncertainty due to assumptions (that is, lack of information)? (4) what are the appropriate method and tools for an integrated validation of WDSN evolution, measurement-based decision making and self-healing? The novelty and significance of my research lies in the development of new formal framework that enables modeling and analysis of WEB-based dynamic social networks (WDSN) with emphasis on time and self-healing. It will explicitly make use of measurement-informed probabilistic reasoning and decision-making about the evolving structure of social interactions and interaction patterns.