Plot Network Data in R with iGraph

I recently had a conversation on Twitter about a plot I made a while back. Recall, the plot showed my Twitter network, my friends and my friend’s friends.

Here’s the Twitter thread:

And here’s the R code:

#### Load R libraries
library("iGraph")

#### Load edgelist
r <- read.csv(file="edgelist_friends.csv-03-25.csv",header=TRUE,stringsAsFactors=FALSE)[,-1]

#### Convert to graph object
gr <- graph.data.frame(r,directed=TRUE)

#### gr
# Describe graph
summary(gr)
ecount(gr) # Edge count
vcount(gr) # Node count
diameter(gr) # Network diameter
farthest.nodes(gr) # Nodes furthest apart
V(gr)$indegree = degree(gr,mode="in") # Calculate indegree

#### Plot graph
E(gr)$color = "gray"
E(gr)$width = .5
E(gr)$arrow.width = .25
V(gr)$label.color = "black"
V(gr)$color = "dodgerblue"
V(gr)$size = 4

set.seed(40134541)
l <- layout.fruchterman.reingold(gr)

pdf("network_friends_plot.pdf")
plot(gr,layout=l,rescale=TRUE,axes=FALSE,ylim=c(-1,1),asp=0,vertex.label=NA)
dev.off()
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Plot and Highlight All Clique Triads in VISONE

snaCliques

Description

This post describes how to identify group structures among a network of respondents in VISONE. For a network of selections we identify any cliques involving three or more members. A clique is defined as a group containing three or more members where everyone has chosen everyone else.

Identify all triads

A tried is a network structure containing exactly three members. There are many types of triads. A group of three members where everyone chooses everyone else is a triad (i.e., a clique). A group of three members where two people choose each other and nobody choose the third member is another type of triad. There are 16 unique ways three people can select each other.

Identify all triads. Click the ‘analysis’ tab. Next to ‘task’, select ‘grouping’ from the drop down list of available options. Select ‘cohesiveness’ from the drop down list next to ‘class’. Select the option ‘triad census’ next to ‘measure’. Click ‘analyze’.

Highlight all cliques

Highlight all cliques. Click an empty part of the graph. Press the keys ‘Ctrl’ and ‘a’. Open the attribute manager. Click the ‘link’ button. Click the ‘filter’ button. Select ‘default value’ from the first drop down list. Select ‘triadType300’ from the second drop down list. Select ‘has individual value’ from the third drop down list. Click the radial button ‘replace’. Click ‘select’. Click ‘close’.

From the main VISONE drop down bar, select ‘links’. Click ‘properties’. Click the given color next to ‘color:’. Select ‘rgb’ tab. Set the ‘red’, ‘green’, and ‘blue’ values to 0. Set the ‘alpha’ value to 255. Set ‘opacity’ to 50%. Click the ‘close’ button. Set the ‘width:’ value to 5.0. From the ‘edge properties’ dialogue box, click the ‘apply’ button. Click ‘close.

Reduce visibility of all non-clique selections. Select all nodes and links. Click an empty part of the graph. Press the keys ‘Ctrl’ and ‘a’. Open the attribute manager. Click the ‘link’ button. Click the ‘filter’ button. Select ‘default value’ from the first drop down list. Select ‘triadType300’ from the second drop down list. Select ‘has individual value’ from the third drop down list. Click the radial button ‘remove’. Click ‘select’. Click ‘close’.

From the main VISONE drop down bar, select ‘links’. Click ‘properties’. Click the given color next to ‘color:’. Set ‘opacity’ to 20%. Set the ‘width:’ value to 2.0. From the ‘edge properties’ dialogue box, click the ‘apply’ button. Click ‘close.

How to extract a network subgraph using R

In a previous post I wrote about highlighting a subgraph of a larger network graph. In response to this post, I was asked how extract a subgraph from a larger graph while retaining all essential characteristics among the extracted nodes.

Vinay wrote:

Dear Will,
The code is well written and only highlights the members of a subgraph. I need to fetch them out from the main graph as a separate subgraph (including nodes and edges). Any suggestions please.

Thanks.

Extract subgraph
For a given list of subgraph members, we can extract their essential characteristics (i.e., tie structure and attributes) from a larger graph using the iGraph function induced.subgraph(). For instance,

library(igraph)                   # Load R packages

set.seed(654654)                  # Set seed value, for reproducibility
g <- graph.ring(10)               # Generate random graph object
E(g)$label <- runif(10,0,1)       # Add an edge attribute

# Plot graph
png('graph.png')
par(mar=c(0,0,0,0))
plot.igraph(g)
dev.off()

g2 <- induced.subgraph(g, 1:7)    # Extract subgraph

# Plot subgraph
png('subgraph.png')
par(mar=c(0,0,0,0))
plot.igraph(g2)
dev.off()

Graph
graph

Subgraph
subgraph