The Topology of Large-Scale Engineering Problem-Solving Networks

The last few years have led to a series of discoveries that uncovered statistical properties, which are common to a variety of diverse real-world social, information, biological and technological networks. The goal of the present paper is to investigate, for the first time, the statistical properties of networks of people engaged in distributed problem solving and discuss their significance. We show that problem-solving networks have properties (sparseness, small world, scaling regimes) that are like those displayed by information, biological and technological networks. More importantly, we demonstrate a previously unreported difference between the distribution of incoming and outgoing links of directed networks. Specifically, the incoming link distributions have sharp cutoffs that are substantially lower than those of the outgoing link distributions (sometimes the outgoing cutoffs are not even present). This asymmetry can be explained by considering the dynamical interactions that take place in distributed problem solving, and may be related to differences between the actor's capacity to process information provided by others and the actor's capacity to transmit information over the network. We conjecture that the asymmetric link distribution is likely to hold for other human or non-human directed networks as well when nodes represent information processing/using elements