Communication Network Design: Balancing Modularity and Mixing via Optimal Graph Spectra

By leveraging information technologies, organizations now have the ability to design their communication networks and crowdsourcing platforms to pursue various performance goals, but existing research on network design does not account for the specific features of social networks, such as the notion of teams. We fill this gap by demonstrating how desirable aspects of organizational structure can be mapped parsimoniously onto the spectrum of the graph Laplacian allowing the specification of structural objectives and build on recent advances in non-convex programming to optimize them. This design framework is general, but we focus here on the problem of creating graphs that balance high modularity and low mixing time, and show how "liaisons" rather than brokers maximize this objective.

Keywords: Optimal Networks, Network Design, Social Networks, Organization Design, Spectral Graph Theory, Modularity, Semi-Definite Programming, Human Computation, Crowdsourcing

JEL Classification: C61, L23

Suggested Citation: Suggested Citation

Lubin, Benjamin and Shore, Jesse and Ishakian, Vatche, Communication Network Design: Balancing Modularity and Mixing via Optimal Graph Spectra (August 17, 2013). Boston U. School of Management Research Paper No. 2013-7, Available at SSRN: https://ssrn.com/abstract=2311755 or http://dx.doi.org/10.2139/ssrn.2311755