if (!require("igraph")) install.packages("igraph", repos="https://cran.cnr.berkeley.edu/", dependencies = TRUE)
library("igraph") # load the required library
# DATASET edgelist
setwd(working_path)
nodes <- read.csv("Dataset1-Media-Example-NODES.csv", header=T, as.is=T)
links <- read.csv("Dataset1-Media-Example-EDGES.csv", header=T, as.is=T)
# What the nodes file look like BEFORE aggregation
head(nodes)
## id media media.type type.label audience.size
## 1 s01 NY Times 1 Newspaper 20
## 2 s02 Washington Post 1 Newspaper 25
## 3 s03 Wall Street Journal 1 Newspaper 30
## 4 s04 USA Today 1 Newspaper 32
## 5 s05 LA Times 1 Newspaper 20
## 6 s06 New York Post 1 Newspaper 50
# What the links file look like BEFORE aggregation
head(links)
## from to weight type
## 1 s01 s02 10 hyperlink
## 2 s01 s02 12 hyperlink
## 3 s01 s03 22 hyperlink
## 4 s01 s04 21 hyperlink
## 5 s04 s11 22 mention
## 6 s05 s15 21 mention
links <- aggregate(weight ~ from + to + type, data = links, sum)
links <- links[order(links$from, links$to),] # Sort by from and to
# What the links file look like AFTER aggregation
head(links)
## from to type weight
## 4 s01 s02 hyperlink 22
## 6 s01 s03 hyperlink 22
## 11 s01 s04 hyperlink 21
## 44 s01 s15 mention 20
## 1 s02 s01 hyperlink 23
## 7 s02 s03 hyperlink 21
# Import edgelist
net <- graph.data.frame(links, nodes, directed=T)
net # showing what net looks like
## IGRAPH 6bf0a9a DNW- 17 49 --
## + attr: name (v/c), media (v/c), media.type (v/n), type.label
## | (v/c), audience.size (v/n), type (e/c), weight (e/n)
## + edges from 6bf0a9a (vertex names):
## [1] s01->s02 s01->s03 s01->s04 s01->s15 s02->s01 s02->s03 s02->s09
## [8] s02->s10 s03->s01 s03->s04 s03->s05 s03->s08 s03->s10 s03->s11
## [15] s03->s12 s04->s03 s04->s06 s04->s11 s04->s12 s04->s17 s05->s01
## [22] s05->s02 s05->s09 s05->s15 s06->s06 s06->s16 s06->s17 s07->s03
## [29] s07->s08 s07->s10 s07->s14 s08->s03 s08->s07 s08->s09 s09->s10
## [36] s10->s03 s12->s06 s12->s13 s12->s14 s13->s12 s13->s17 s14->s11
## [43] s14->s13 s15->s01 s15->s04 s15->s06 s16->s06 s16->s17 s17->s04
V(net)$name <- V(net)$media
## Showing
degree(net,mode = c("all"))
## NY Times Washington Post Wall Street Journal
## 8 6 13
## USA Today LA Times New York Post
## 9 5 8
## CNN MSNBC FOX News
## 5 5 4
## ABC BBC Yahoo News
## 5 3 6
## Google News Reuters.com NYTimes.com
## 4 4 5
## WashingtonPost.com AOL.com
## 3 5
betweenness(net)
## NY Times Washington Post Wall Street Journal
## 17.666667 1.000000 144.500000
## USA Today LA Times New York Post
## 97.000000 50.000000 21.500000
## CNN MSNBC FOX News
## 0.500000 14.000000 1.000000
## ABC BBC Yahoo News
## 29.000000 0.000000 41.500000
## Google News Reuters.com NYTimes.com
## 21.500000 1.000000 4.666667
## WashingtonPost.com AOL.com
## 0.000000 66.000000
## igraph plot
plot(net,vertex.size=10, edge.arrow.size=.2, edge.curved=0,vertex.color='orange', vertex.frame.color='#555555', vertex.label.color='blue',vertex.label.cex=.7)
## igraph plot with node color
plot(net,vertex.size=10, edge.arrow.size=.2, edge.curved=0,vertex.color='pink', vertex.frame.color='#555555', vertex.label.color='blue',vertex.label.cex=.7)
## igraph plot with various size
plot(net,vertex.size=V(net)$audience.size, edge.arrow.size=.2, edge.curved=0,vertex.color='orange', vertex.frame.color='#555555', vertex.label.color='blue',vertex.label.cex=.7)
## igraph plot with specific layout
# Random layout
plot(net,layout=layout.random, vertex.size=V(net)$audience.size,edge.arrow.size=.2, edge.curved=0,vertex.color='orange', vertex.frame.color='#555555', vertex.label.color='blue',vertex.label.cex=.7)
L_fr <- layout_with_fr(net) # Fruchterman-Reingold layout algorithm
head(L_fr)
## [,1] [,2]
## [1,] 1.42125506 0.04396139
## [2,] 1.79047344 -0.11648445
## [3,] 1.65538465 0.36987635
## [4,] 1.18493263 0.59282030
## [5,] 1.59078261 -0.52771621
## [6,] 0.03966739 0.59301819
plot(net,vertex.size=V(net)$audience.size,layout=L_fr,edge.arrow.size=.2, edge.curved=0,vertex.color='orange', vertex.frame.color='#555555', vertex.label.color='blue',vertex.label.cex=.7)
## Change background color
par(bg = 'black')
plot(net,vertex.size=V(net)$audience.size,layout=L_fr,edge.arrow.size=.2, edge.curved=0,vertex.color='orange', vertex.frame.color='#555555', vertex.label.color='white',vertex.label.cex=.7)
## No fixed aspect ratio
par(bg = 'black')
plot(net,vertex.size=V(net)$audience.size,layout=L_fr,edge.arrow.size=.2, edge.curved=0,vertex.color='orange', vertex.frame.color='#555555', vertex.label.color='white',vertex.label.cex=.7,asp=0)
wc <- walktrap.community(net)
dendPlot(wc, mode="hclust") # Create a dendrogram
plot(wc, net, vertex.size=5, vertex.label.cex=.7, edge.arrow.size=.2, edge.curved=0)
membership(wc)
## NY Times Washington Post Wall Street Journal
## 1 1 1
## USA Today LA Times New York Post
## 1 1 3
## CNN MSNBC FOX News
## 2 2 2
## ABC BBC Yahoo News
## 2 1 4
## Google News Reuters.com NYTimes.com
## 4 4 1
## WashingtonPost.com AOL.com
## 3 3
V(net)$grp_member <- membership(wc)
## Plotly
if (!require("plotly")) install.packages("plotly", repos="https://cran.cnr.berkeley.edu/", dependencies = TRUE)
library(plotly)
Xn <- L_fr[,1]
Yn <- L_fr[,2]
es <- as.data.frame(get.edgelist(net))
edge_shapes <- list() # Prepare a empty list
for(i in 1:length(E(net))) {
v0 <- es[i,]$V1
v1 <- es[i,]$V2
edge_shape <- list(
type = "line",
line = list(color = "#030303", width = 0.3),
x0 = Xn[v0],
y0 = Yn[v0],
x1 = Xn[v1],
y1 = Yn[v1]
)
edge_shapes[[i]] <- edge_shape
}
a <- list(
showarrow=TRUE,
arrowhead=3,
arrowsize=1,
arrowwidth=1.5,
arrowcolor='#636363'
)
network <- plot_ly()
network <- add_markers(network, x = ~Xn, y = ~Yn, color = V(net)$grp_member, mode = "markers", marker = list(size = V(net)$audience.size, annotations = a), text = V(net)$name, hoverinfo = "text")
axis <- list(title = "", showgrid = FALSE, showticklabels = FALSE, zeroline = FALSE) # Don't display axis and tick labels
p <- layout(network,
title = 'Media Network in Plotly',
shapes = edge_shapes,
xaxis = axis,
yaxis = axis
)
p <- hide_colorbar(p) # Don't display color bar
p
## Network Visualization using D3
if (!require("networkD3")) install.packages("networkD3", repos="https://cran.cnr.berkeley.edu/", dependencies = TRUE)
library(networkD3)
edgeList <- get.data.frame(net,"edges")
nodeList <- get.data.frame(net,"vertices")
edgeList$SourceID <- match(edgeList$from, nodeList$name)-1
edgeList$TargetID <- match(edgeList$to, nodeList$name)-1
D3_network <- networkD3::forceNetwork(
Links = edgeList, # data frame that contains info about edges
Nodes = nodeList, # data frame that contains info about nodes
Source = "SourceID", # ID of source node
Target = "TargetID", # ID of target node
NodeID = "name", # display value from the node list (e.g., node name)
Group = "grp_member", # value we want to use for node color
Value = "weight",
Nodesize = "audience.size", # node size according to audience size
charge = -500,
height = 500, # Size of the plot (vertical)
width = 1000, # Size of the plot (horizontal)
fontSize = 50, # Font size
linkWidth = 1, # Link width
zoom = TRUE # ability to zoom when click on the node
)
# Plot network
D3_network
# Rescaling the node size
nsize_max <- max(nodeList$audience.size)
nsize_min <- min(nodeList$audience.size)
max_size <- 500
nodeList$audience.size1 <- max_size*(nodeList$audience.size-nsize_min)/(nsize_max-nsize_min)
D3_network <- networkD3::forceNetwork(
Links = edgeList, # data frame that contains info about edges
Nodes = nodeList, # data frame that contains info about nodes
Source = "SourceID", # ID of source node
Target = "TargetID", # ID of target node
NodeID = "name", # display value from the node list (e.g., node name)
Group = "grp_member", # value we want to use for node color
Value = "weight",
Nodesize = "audience.size1", # node size according to audience size
charge = -500,
height = 500, # Size of the plot (vertical)
width = 1000, # Size of the plot (horizontal)
fontSize = 50, # Font size
linkWidth = 1, # Link width
zoom = TRUE # ability to zoom when click on the node
)
D3_network
# Save your work in html
#networkD3::saveNetwork(D3_network_LM, "D3_LM.html", selfcontained = TRUE)