UCL School of Management

Research project

Topology and evolution of networks

Summary

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.

Relevance

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.

Selected publications

Kang, S. M. (2007). A note on measures of similarity based on centrality. Social Networks, 29 (1), 137-142. doi:10.1016/j.socnet.2006.04.004 [link]
Kang, S. M. (2007). Equicentrality and network centralization: A micro–macro linkage. Social Networks, 29 (4), 585-601. doi:10.1016/j.socnet.2007.07.004 [link]
Roth, C., Kang, S. M., Batty, M., & Barthelemy, M. (2012). A long-time limit for world subway networks. Journal of the Royal Society Interface, 9 (75), 2540-2550. doi:10.1098/​rsif.2012.0259 [link]

Link to the publication’s UCL Discovery page

Last updated Thursday, 6 August 2015

Author

Research groups

Strategy & Entrepreneurship; Operations and Technology

Research areas

Management science; Operations management; Organization theory

Research topics

Big-data analytics; Complex systems; Inter-organizational networks; Interpersonal networks; Intra-organizational networks; Knowledge networks; Social network microfoundations; Transportation; Supply chain management