Find books, journal articles and other MelNet publications
Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. This edited volume provides a self-contained, exhaustive account of the theoretical and methodological underpinnings of ERGMs.
Doing Social Network Research
With straight-forward guidance on research design and data collection, as well as social network analysis, this book takes you start to finish through the whole process of doing network research.
Networks provide a more complex representation of interdependence. In our research we extend exponential random graph models (ERGMs) to multilevel networks. We present a general formulation of a multilevel network structure.
See our representative list of publications by the MelNet team below
Bryant, R.A., Gallagher, H. C., Gibbs, L., Pattison, P. … Lusher, D. (2017). Mental health and social networks following disaster. American Journal of Psychiatry. Advance online publication.
Gallagher, H. C., & Robins, G. (2015). Network statistical models for language learning contexts: Exponential random graph models and willingness to communicate. Language Learning, 65 (4), 929-962.
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. (2016): The interplay between formal project memberships and informal advice seeking in knowledge-intensive firms: A multilevel network approach. Social Networks
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., Koskinen, J., & Robins, G. (Eds.). (2013). Exponential Random Graph Models for Social Networks: Theory, Methods and Applications. New York: Cambridge University Press.
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.
Pattison, & Robins, G. (2002). Neighbourhood-based models for social networks. Sociological Methodology, 32, 301-337.
Pattison, & Wasserman, S. (1999). Logit models and logistic regressions for social networks: II. Multivariate relations. British Journal of Mathematical & Statistical Psychology, 52, 169-193.
Robins, G. (2015). Doing Social Networks Research: Network Research Design for Social Scientists. Los Angeles: Sage.
Robins, G., & Morris, M. (2007). Advances in exponential random graph (p*) models. Social Networks, 29(2), 169-172.
Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2), 173-191.
Robins, G., Pattison, P., & Wang, P. (2009). Closure, connectivity and degree distributions: Exponential random graph (p*) models for directed social networks. Social Networks, 31(2), 105-117. doi: 10.1016/j.socnet.2008.10.006
Robins, G., Snijders, T., Wang, P., Handcock, M., & Pattison, P. (2007). Recent developments in exponential random graph (p*) models for social networks. Social Networks, 29(2), 192-215. doi: 10.1016/j.socnet.2006.08.003
Snijders, T. A. B., Pattison, P. E., Robins, G. L., & Handcock, M. S. (2006). New specifications for exponential random graph models. In R. M. Stolzenberg (Ed.), Sociological Methodology 2006, Vol 36 (Vol. 36, pp. 99-153).
Wang, P., Robins, G., Pattison, P., & Lazega, E. (2013). Exponential random graph models for multilevel networks. Social Networks, 35(1), 96-115.
Wang, P., Sharpe, K., Robins, G. L., & Pattison, P. E. (2009). Exponential random graph (p*) models for affiliation networks. Social Networks, 31(1), 12-25.