Difference between revisions of "Social Network Analysis With Igraph Package Using R"

Latest revision as of 12:43, 16 March 2011

Install the package under R environmemnt

under Ubuntu install the R package:

sudo apt-get install r-base-core

type R to start the program:

R

type the command to download and install igraph as R library:

install.packages("igraph")

Starting with the package

don't forget to load the library:

library('igraph')

parse a network file in Pajek format and access to its memory representation through the variable 'g':

g <- read.graph(file='/your/path/.../file.net', format='pajek')

list vertex and their attributes of graph g:

V(g)                      # the list of all nodes
V(g)[0]                   # access the first node
list.vertex.attributes(g) # the list of all vertex attributes names
V(g)[0]$id                # access the attribute 'id' for the first node

list edges/arcs and their attributes of graph g:

E(g)                      # the list of all edges/arcs
E(g)[0]                   # access the first edge/arc
list.edge.attributes(g)   # the list of all edges/arcs attributes names
E(g)[0]$weight            # access the attribute 'weight' for the first node

draw the graph:

plot(g)
tkplot(g)

Macroscopic Analysis

graph size (number of nodes): length(V(g))

number of edges: length(E(g))

diameter: diameter(g)

mean degree:

density:

giant component size (the largest connected component size):

assortativity:

Node Centrality Analysis

degree: degree(g)

closeness: closeness(g)

betweenness: betweenness(g)

eigenvector/pagerank: evcent(g)

Clustering Techniques

connected components: clusters(g)

edge betweenness:

walktrap:

spinglass:

References and further informations

Igraph/R documentation: http://igraph.sourceforge.net/doc/R/00Index.html