| Member Profile : Garry Robins |
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 | Contact Information | Address: -Map Me-
Garry Robins
University of Melbourne, Psychological Sciences
Psychological Sciences
University of Melbourne
Melbourne, Victoria, Australia 3010
Phone : 61 3 8344 4454
Fax : 61 3 9347 6618
E-mail : garrylr@unimelb.edu.au
Website : http://www.sna.unimelb.edu.au/
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| Bibliographic Information |
Pattison, P. & Robins, G. (2008). Probabilistic network theory.. Rudas, T, (Eds.). Handbook of Probability: Theory and Applications. ( ed.). Sage
Pattison, P., Robins, G. & Kashima, Y. (2008). Psychology of social networks.. In The New Palgrave Dictionary of Economics, 2nd edition
Robins, G. & Kashima, Y. (2008). Social psychology and social networks.. Asian Journal of Social Psychology, 11, 1-12
Robins, G. & Morris, M. (2007). Advances in exponential random graph (p*) models.. Social Networks, 29, 160-172
Robins, G., Pattison, P., Kalish, Y. & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks (29), 173-191
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, 192-215
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| | | Software & Data | | Active Calendar Listings |
| pnet - program for statistical network modeling | (Software) |
statistical analysis of social network data - especially using exponential random graph models.
Simulation:
Simulate Exponential Random Graph distributions with given parameters.
Estimation:
Approximate specified network effects or parameters for a given network.
Goodness of Fit:
Test parameter estimates of a model against important features of the observed network. |
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| | | Jobs Posted | | Sunbelt Submissions |
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| Sunbelt XXX - June 29 to July 04, 2010 - Riva del Garda Fierecongressi | | Abstract : Activity, closure and brokerage in social network models |
| We describe new specifications for social network statistical models to assist the joint modeling of network activity, closure and brokerage. Actors in a social network have different levels of network activity, as expressed through the degree distribution. But activity can take different structural forms. An ongoing theme in social network theory is the contrast between network closure – the tendency for closed cyclic and clique-like substructures to form within social networks – and network brokerage – the propensity for some ties to bridge between these more closed network regions. Burt (2005) argues that when social capital is optimized, brokerage and closure operate together. Activity and closure processes in empirical social networks can be well represented using current specifications for exponential random graph models. But explicit parameterization of brokerage has to date been undeveloped. We introduce edge-triangle configurations, representing the expression of ties away from closed structures to other parts of the network. By simulation, we provide examples of different types of network brokerage: brokerage through hubs or a core of nodes; brokerage distributed across the network through overlapping group membership; and brokerage through bridging ties. With an empirical example of work collaboration among managers in a government instrumentality, we show how the combination of parameters for activity, closure and brokerage can better fit important network characteristics. |
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