PhD defence: Ivan Belik

On Friday 20 May 2016 Ivan Belik will hold a trial lecture on a prescribed topic and defend his thesis for the PhD degree at NHH.

The dynamic nature of large-scale network formation requires the development of multidisciplinary methods for the effective social network analysis (SNA).

The research is motivated by two general problems. First, SNA employs methods and techniques from originally disconnected research domains, such as graph theory, theory of algorithms, mathematical optimization, game theory, etc. By bridging different fragmented approaches, we get a comprehensive understanding of various concepts and greater flexibility in their usage. Second, modern SNA requires the framework development for the technical (quantitative) analysis. Since many socio-economic systems are characterised by complex and large-scale structures, the need for efficient quantitative methods of high-dimensional data analysis in networks is growing rapidly and, consequently, requires new integrative mechanisms to be developed.

The research is focused on the interdisciplinary theoretical and methodological aspects of SNA - investigating, developing and testing symbiotic socio-technical approaches for the multifaceted world of SNA. Combining the variety of methods from graph theory, comparative SNA and game theory Belik develops the interdisciplinary mechanisms for the comparative network analysis, algorithmic analysis of network centrality computation and leadership formation, Shapley-based Stackelberg competition and stochastic dominance in networks. Based on the mathematical optimization techniques Belik introduces a way to analyze split networks that are some of the most common structures in the real-world large-scale systems. The approaches are tested and illustrated based on different types of topologies and real-life networks.

Prescribed topic for the trial lecture

Explain the small world phenomenon, and explain the opportunities for descriptive and prescriptive analyses of this phenomenon in social networks in an organisational setting. Also, highlight the implications of the research described in the thesis on small worlds for management practice