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In the last decade, there has been a massive increase in network research across both the social and physical sciences. In Physics and Mathematics, there have been extensive work on phenomenological models and generative models concerning large networks with applications to biology and social networks. In the social sciences, on the other hand, much attention has been devoted to the study of personal networks (PN) which examine the ties an individual has with others and their social characteristics and dynamics. In this paper, we seek to bridge the gap between social and mathematical sciences by exploring how variation in personal network size influences information flow through a complete network. We find that there is a significant negative correlation between a particular combination of personality traits and personal network size. A simulation modelling information flow through a complete network reveals that a mixture of small and large personal networks produces the optimal relative convergence rate at which information disseminates through the networks. © 2009 IEEE.

Original publication




Journal article


Proceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009

Publication Date





188 - 193