Mitchell centre seminar series
| Dates: | 3 April 2019 |
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| Times: | 16:00 - 17:30 |
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| What is it: | Seminar |
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| Organiser: | School of Social Sciences |
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| Speaker: | Alex Stivala |
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Alex Stivala, Swinburne University of Technology
ERGM parameter estimation of very large directed networks: implementation, example, and application to the geography of knowledge spillovers
The recently published Equilibrium Expectation (EE) algorithm for exponential random graph model (ERGM) parameter estimation has allowed such models to be estimated for networks far larger than previously possible. Here we demonstrate the extension of this algorithm to directed networks, with an implementation that overcomes some technical problems limiting the sizes of networks that could be practically estimated. We apply this method to estimate ERGM parameters for an online social network with approximately 1.6 million nodes, and a patent citation network with approximately 3.8 million nodes. The latter model allows us to test the geographic knowledge spillover hypothesis (that knowledge spillovers are geographically localized) using patent citation data, without having to treat the patent citation network as exogenous.
Speaker
Alex Stivala
Organisation: Swinburne University of Technology
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G7
Humanities Bridgeford Street
Manchester
