View source for Social Network Analysis With Igraph Package Using R

== Install the package under R environmemnt ==

under Ubuntu install the R package:
 <code>sudo apt-get install r-base-core</code>

type R to start the program:
 <code>R</code>

type the command to download and install igraph as R library:
 <code>install.packages("igraph")</code>

== Starting with the package ==
don't forget to load the library:
 <code>library('igraph')</code>
parse a network file in Pajek format and access to its memory representation through the variable 'g':
 <code>g <- read.graph(file='/your/path/.../file.net', format='pajek')</code>
list vertex and their attributes of graph g:
 <code>
 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]$id                # access the attribute 'id' for the first node
 </code>
list edges/arcs and their attributes of graph g:
<code>
 E(g)                      # the list of all edges/arcs
 E(g)[0]                   # access the first edge/arc
 list.edge.attributes(g)   # the list of all edges/arcs attributes names
 E(g)[0]$weight            # access the attribute 'weight' for the first node
 </code>
draw the graph:
<code>
 plot(g)
</code>

== 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):

== Node Centrality Analysis ==

degree:

closeness:

betweenness:

eigenvector/pagerank:

assortativity:

== Clustering Techniques ==

connected components:

edge betweenness:

walktrap:

spinglass:

== References and further informations ==

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

[[Category:Tutorial]]