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PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3-
 M3//EN
VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20191113T223539Z
DTSTART:20190403T150000Z
DTEND:20190403T163000Z
SUMMARY:Mitchell centre seminar series
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}l7r-joyhyr5
 y-k8t83b
DESCRIPTION:Alex Stivala\, Swinburne University of Technology\n\nERGM par
 ameter estimation of very large directed networks: implementation\, exam
 ple\, and application to the geography of knowledge spillovers\n\nThe re
 cently published Equilibrium Expectation (EE) algorithm for exponential 
 random graph model (ERGM) parameter estimation has allowed such models t
 o 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 s
 izes of networks that could be practically estimated. We apply this meth
 od to estimate ERGM parameters for an online social network with approxi
 mately 1.6 million nodes\, and a patent citation network with approximat
 ely 3.8 million nodes. The latter model allows us to test the geographic
  knowledge spillover hypothesis (that knowledge spillovers are geographi
 cally localized) using patent citation data\, without having to treat th
 e patent citation network as exogenous.  
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:G7\, Humanities Bridgeford Street\, Manchester
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