What we do

We investigate the structure and dynamics of social networks, with a joint focus on method and application. We work on the development of cutting-edge statistical models for social network analysis, notably exponential random graph models (ERGM). These network models enable us to understand critical issues of importance to organisations and communities, such as innovation, trust and culture. We key areas of academic research are ERGM, networks and organisations, multilevel networks, and network dynamics.

Our major current research interests include:

Exponential Random graph models (ERGM)

ERGMs are prominent statistical models for social network structures. They take into account important endogenous structural effects such as network closure, degree centralisation, and reciprocity; and actor-relation (attribute) effects such as homophilly, and sender and receiver effects.

We also develop autologistic actor attribute models (ALAAMs), which can predict actor attributes from network structure and so model effects such as contagion and social influence. The theoretical implications of ERGMs are also an element of this work.


  • Lusher, D., Koskinen, J., & Robins, G. (Eds.). (2013). Exponential Random Graph Models for Social Networks: Theory, Methods and Applications. New York: Cambridge University Press.
  • Gallagher, C., & Robins, G. (in press). Network statistical models for language learning contexts: Exponential random graph models and the Willingness to Communicate. Language Learning.

Multilevel networks

A two-level network involves nodes at two different levels with different types of ties within and between the levels. This data structure can be used to represent many social systems that involve both hierarchy/level and networks, particularly organisations but also novel applications such as social-ecological systems. We have developed ERGMs for multilevel networks.


  • Wang, P., Robins, G., Pattison, P., & Lazega, E. (2013). Exponential random graph modules for multilevel networks. Social Networks, 35(1), 96-115
  • Brailly J., Favre G., Chatellet J., Lazega E., 2015, Embeddedness as a Multilevel Problem. A Case Study in Economic Sociology. Social Networks
  • Brennecke, J. & Rank, O.N. (forthcoming). The interplay between formal project memberships and informal advice seeking in knowledge-intensive firms: A multilevel network approach. Social Networks, dx.doi.org/10.1016/j.socnet.2015.02.00

Big data networks

We are investigating inference for big data using parallel estimation of multiple snowball samples, in conjunction with colleagues from the University Svizzeria Italia (University of Lugano, Switzerland) and Northwestern University.


  • Pattison, P., Robins, G., Snijders, T. & Wang, P. (2013). Conditional estimatation of exponential random graph models from snowball and other sampling designs. Journal of Mathematical Psychology, 57, 284-296
  • Stivala, A., Koskinen, J., Rolls, D., Wang, P., & Robins, G. (2016). Snowball sampling for estimating exponential random graph models for large networks.  Social Networks, 47, 167-188.

Networked innovation

Innovation no longer belongs to stand-alone corporate or government research and development (R&D) laboratories. It is the property of networks, where innovation occurs at the interstices of organisations, large and small, public and private, and the individuals nested within. These networks operate at intra- and inter-organisational, regional, national and international levels. Our research partners include the Commonwealth Scientific and Industrial Research Organisation (CSIRO), the Boeing Company, AusBiotech and the Australian Football League.


  • Brennecke, J., Rank, O. N. (forthcoming): The interplay between formal project memberships and informal advice seeking in knowledge-intensive firms: A multilevel network approach. Social Networks,dx.doi.org/10.1016/j.socnet.2015.02.004
  • Lomi, A., Lusher, D., Pattison, P., Robins, G. L. (2014). The focused organization of advice relations: A case study of boundary-crossing ties in a multi-unit business group. Organization Science, 25(2).
  • Lusher, D., Robins, G, Pattison, P., Lomi, A. (2012). "Trust Me": Social Mechanisms for Expressed and Perceived Trust in an Organization. Social Networks, 34, 410-424
  • Gilding, M. (2008). 'The tyranny of distance': biotechnology networks and clusters in the Antipodes. Research Policy, Vol. 37, no. 6-7 (Jul 2008), pp. 1132-1144.


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