Network-Analysis/Unipartite network analysis at master · rakshitb/Network-Analysis · GitHub

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# Package igraph
library(igraph)

# Read Data through CSV files
data=read.csv(file.choose(),header = T)

# Convert into a data frame
y<-data.frame(data)

# Create Network: A directed graph
net<-graph.data.frame(y,directed=T)

# Vertices and Edges: Details
V(net)
E(net)
V(net)$label<-V(net)$name #Vertex labels
V(net)$degree<-degree(net)# Vertex degree
degdata=data.frame(V(net)$label,V(net)$degree)

# Centrality Measures
indegree=degree(net,mode='in')
#indegree

outdegree=degree(net,mode='out')
#outdegree

totaldegree=degree(net)

'Closeness Centrality'
closcen=closeness(net)

'Betweeness Centrality'
betcen=betweenness(net)

'Eigen-Vector Centrality'
eigcen=eigen_centrality(net)

'Clustering coefficent for each node'
clucoeff=transitivity(net,type="local")

# Graph Density, Number of Vertices, edges, and Largest connected component

gdensity=edge_density(net)
nvertices=gorder(net)
nlinks=gsize(net)

'Connected component'
c=clusters(net)
lcomponent=max(c$csize)


# Data frame consiting the various parameters for each vertices
#centraldta=data.frame(V(net)$label,totaldegree,indegree,outdegree,closcen,betcen,clucoeff,eigcen)

# Writng the above data frame into a csv file
#write.csv(centraldta,file='D:/Intern/Indian Board Data/Indian Board Data/calculated measures/unipartite/directors/network_2015.csv',row.names = FALSE)


#### Code to calculate parameters for unipartite networks ####

'Structural Equivalence'
# In order to calculate structural equivalence,
# I called on the network to be undirected rather than directed

# Loading package conCor from github
library(devtools)
devtools::install_github("aslez/concoR")
library(concoR)
library(igraph)


# Concor package is used for calculating structural equivalence of nodes in social network
# http://tagteam.harvard.edu/hub_feeds/2011/feed_items/2100977
# https://rpubs.com/pjmurphy/325575

# Convert into a data frame
y1<-data.frame(data)

# Create Network: An undirected graph
net1<-graph.data.frame(y1,directed=FALSE)

# Converting the matrix into adjancey matrix
mat <- as.matrix(get.adjacency(net1))

# Calling on the concor_hca function to calculate structural equivalence
ste=concor_hca(list(mat),p=2)