Basic SNA with R
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Basic SNA with R
Introduction to Social Network Analysis with R Part 2: Basic SNA with R Michal Bojanowski ICM, University of Warsaw [email protected] March 13, 2012 Sunbelt XXXII, Redondo Beach, CA, USA Outline of the Part 2 1 Network data and manipulation 2 Network visualization 3 Some SNA routines Focus on igraph with pointers to network. Michal Bojanowski Introduction to SNA with R ICM UW Network of network-related packages in R DCGL cccdmixOmics cMonkey paloma biGraph ebdbNet osmar packdep GeneReg c3net NetworkAnalysis mfr gRim ARTIVA oposSOM RC pathClass rEMM catnet CDVine QuACN BiomarkeR PoMoS dpa iRefR gRbase editrules FrF2 BiGGR G1DBN iSubpathwayMiner igraph RQDA ISIPTA ggm isa2 rgp epoc GOSim linkcomm igraphtosonia gstudio timeordered ppstat TunePareto gdistance phangorn ppiPre RNetLogo triads Matrix fanovaGraph kknndiffusionMap BoolNet arulesVizRGraphics NetComp huge raster tnet bipartite intergraph GeneNet msSurv proto RnavGraph gRain gRapHD gMCP bnlearn PairViz proftools PerfMeas kBestShortestPaths DOSim NetPreProc ddepn gRc graph pcalg classGraph psych rattle RSiena ergm network sna VBLPCM GGMselectsnort statnet mpa ergm.userterms Bergm networkDynamic networksis epinet latentnet degreenet rDNA Michal Bojanowski Introduction to SNA with R ICM UW Data used in part 2 io Directed weighted graph of commodity flows between 21 industrial sectors in US (source: Bureau of Economic Analysis) college Undirected binary network of on-line friendship relations among students of a college. Michal Bojanowski Introduction to SNA with R ICM UW