Correlations in Bipartite Collaboration Networks

Abstract

Collaboration networks are studied as an example of growing bipartite networks. These have been previously observed to have structure such as positive correlations between nearest-neighbour degrees. However, a detailed understanding of the origin of this phenomenon and the growth dynamics is lacking. Both of these are analyzed empirically and simulated using various models. A new one is presented, incorporating empirically necessary ingredients such as bipartiteness and sublinear preferential attachment. This, and a recently proposed model of team assembly both agree roughly with some empirical observations and fail in several others.

13 pages, 17 figures, 2 table, submitted to JSTAT; manuscript reorganized, figures and a table added

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• The reinforcing influence of recommendations on global diversification
• Emergence of a non-scaling degree distribution in bipartite networks: a numerical and analytical study
• Modeling Discrete Combinatorial Systems as Alphabetic Bipartite Networks: Theory and Applications
• A self-consistent approach to measure preferential attachment in networks and its application to an inherent structure network
• Explicit mutual information for simple networks and neurons with lognormal activities