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