Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Statistical evaluation of algebraic constraints for social networks
Journal of Mathematical Psychology
Nexus: Small Worlds and the Groundbreaking Theory of Networks
Nexus: Small Worlds and the Groundbreaking Theory of Networks
The small core of the German corporate board network
Computational & Mathematical Organization Theory
Business intelligence approach to support modelling and analysis of complex economic networks
International Journal of Networking and Virtual Organisations
Visual analysis of bipartite biological networks
EG VCBM'08 Proceedings of the First Eurographics conference on Visual Computing for Biomedicine
Detecting community structure in bipartite networks based on matrix factorisation
International Journal of Wireless and Mobile Computing
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We describe a methodology to examine bipartite relational data structures as exemplified in networks of corporate interlocking. These structures can be represented as bipartite graphs of directors and companies, but direct comparison of empirical datasets is often problematic because graphs have different numbers of nodes and different densities. We compare empirical bipartite graphs to simulated random graph distributions conditional on constraints implicit in the observed datasets. We examine bipartite graphs directly, rather than simply converting them to two 1-mode graphs, allowing investigation of bipartite statistics important to connection redundancy and bipartite connectivity. We introduce a new bipartite clustering coefficient that measures tendencies for localized bipartite cycles. This coefficient can be interpreted as an indicator of inter-company and inter-director closeness; but high levels of bipartite clustering have a cost for long range connectivity. We also investigate degree distributions, path lengths, and counts of localized subgraphs. Using this new approach, we compare global structural properties of US and Australian interlocking company directors. By comparing observed statistics against those from the simulations, we assess how the observed graphs are structured, and make comparisons between them relative to the simulated graph distributions. We conclude that the two networks share many similarities and some differences. Notably, both structures tend to be influenced by the clustering of directors on boards, more than by the accumulation of board seats by individual directors; that shared multiple board memberships (multiple interlocks) are an important feature of both infrastructures, detracting from global connectivity (but more so in the Australian case); and that company structural power may be relatively more diffuse in the US structure than in Australia.