Community detection

Network Analysis in R

James Curley

Associate Professor, University of Texas at Austin

Community detection in networks

Fast-greedy detection

fastgreedy.community(g)

IGRAPH clustering fast greedy, 
groups: 3, mod: 0.5
+ groups:
  $`1`
  [1] "A" "B" "C" "D" "E" "F"

  $`2`
  [1] "J" "G" "H" "I" "K" "L"

  $`3`
  [1] "M" "N" "O" "P"

Edge-betweenness detection

edge.betweenness.community(g)

IGRAPH clustering edge betweenness, 
groups: 3, mod: 0.5
+ groups:
  $`1`
  [1] "A" "B" "C" "D" "E" "F"

  $`2`
  [1] "J" "G" "H" "I" "K" "L"

  $`3`
  [1] "M" "N" "O" "P"

x <- fastgreedy.community(g)
length(x)

[1] 3

sizes(x)

Community sizes
1 2 3 
6 6 4

membership(x)

A B C D E F J G H I K L M N O P 
1 1 1 1 1 1 2 2 2 2 2 2 3 3 3 3

plot(x, g)

Let's practice!

Network Analysis in R