Several measures have been proposed in the past to capture certain topological characteristics of the networks. But, how well they describe specific phenomena has received less attention. This research investigates their appropriateness and formulates new measures that are empirically more accurate. In particular, from a micro-level, we measure how nodes in a network tend to link to other nodes depending on their centrality. We examine how this micro-level phenomenon is linked to macro-level structure of the networks as they evolve over time.
Networks are integral part of complex systems we encounter in nature and society. Understanding how single entities or actors are linked to others creating and affecting entire complex systems are relevant to not only the management of businesses and organizations, but also to a diverse range of disciplines, from life sciences to engineering. This research provides methods and models to understand the micro-macro linkage between local behaviors and global patterns of networks.
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