This is the R code used for my M.A. thesis, which is also included as Appendix B in the document itself.

MA_thesis_appendix_b.r

### INITIATE IGRAPH ###

library(igraph)

### LOAD NETWORK DATA ###

dat=read.csv(file.choose(),header=TRUE,row.names=1,check.names=FALSE)

m=as.matrix(dat)

g=graph.adjacency(m,mode="undirected",weighted=TRUE,diag=FALSE)

g

### ADD ATTRIBUTES ###

a=read.csv("attribs.csv") ##### MODIFY THIS FILE PATH AND ATTRIBUTE NAMES IF NECESSARY

V(g)$name=as.character(a$Site[match(V(g)$name,a$SafeName)])

V(g)$site_id=as.character(a$Site.ID[match(V(g)$name,a$Site)])

V(g)$obsi_analyzed=as.character(a$Obsidian.Analyzed[match(V(g)$name,a$Site)])

V(g)$name=as.character(a$Site[match(V(g)$name,a$SafeName)])

V(g)$latitude=as.character(a$Latitude[match(V(g)$name,a$Site)])

V(g)$longitude=as.character(a$Longitude[match(V(g)$name,a$Site)])

V(g)$country=as.character(a$Country[match(V(g)$name,a$Site)])

V(g)$region=as.character(a$Region[match(V(g)$name,a$Site)])

V(g)$period=as.character(a$Period[match(V(g)$name,a$Site)])

### ANALYSIS ###

# Betweenness Centrality
bw=betweenness(g, v=V(g), directed = FALSE, nobigint = TRUE, normalized = TRUE, weights = NULL)
bw
V(g)$betweeness=bw

# Closeness Centrality
clo=closeness(g, vids=V(g), mode = c("all"), weights = NULL, normalized = TRUE)
clo
V(g)$closeness=clo

# Local Clustering Coefficient
cc=transitivity(g, type=c("barrat"), vids = NULL, weights = NULL, isolates = c("zero"))
cc
V(g)$local_cc=cc

# Global Clustering Coefficient
gcc=transitivity(g, type=c("globalundirected"), vids = NULL, weights = NULL, isolates = c("zero"))
gcc
g$global_cc=gcc

# Average Local Clustering Coefficient
acc=transitivity(g, type=c("localaverageundirected"), vids = NULL, isolates = c("zero"))
acc
g$average_local_cc=acc

# Degree
deg=degree(g, v=V(g), mode = c("all"), loops = NULL, normalized = FALSE)
deg
V(g)$degree=deg

# Weighted Degree
wdeg=graph.strength (g, vids = V(g), mode = c("all"), loops = NULL, weights = NULL)
wdeg
V(g)$weighted_degree=wdeg

# Average Degree
adeg=mean(V(g)$degree)
adeg
g$average_degree=adeg

# Average Path Length
apl=average.path.length(g, directed=FALSE, unconnected=TRUE)
apl
g$average_path_length=apl

# Edge Betweenness Communities
ebc=edge.betweenness.community (g, weights = E(g)$weight, directed = FALSE, edge.betweenness = TRUE, merges = TRUE, bridges = TRUE, modularity = TRUE, membership = TRUE)
ebc
V(g)$GN=ebc$membership
g$ebc_modularity=ebc$modularity

# Edge Betweenness
eb=edge.betweenness(g, e=E(g), directed = FALSE, weights = NULL)
eb
E(g)$edge_betweeness=eb

# Density
den=graph.density(g, loops=FALSE)
den
g$density=den

# Diameter
diam=diameter(g, directed = FALSE, unconnected = TRUE, weights = NULL)
diam
g$diameter=diam

# Eccentricity
eccen=eccentricity(g, vids=V(g), mode=c("all"))
eccen
g$eccentricity=eccen

# Radius
rad=radius(g, mode=c("all"))
rad
g$radius=rad

# Number of Triangles
tri=adjacent.triangles (g, vids = V(g))
tri
V(g)$triangles=tri

# Size of Largest Clique
lcli=clique.number(g)
lcli
g$largest_clique=lcli

### WRITE GRAPH TO FILE ###

write.graph(g, "g.gml", format=c("gml")) ##### MODIFY OUTPUT FILE NAMES
write.graph(g, "g.net", format=c("pajek"))

### EDGE-BETWEENNESS COMMUNITIES DENDROGRAM ###

V(g)$name<-V(g)$site_id
ebc=edge.betweenness.community (g, weights = E(g)$weight, directed = FALSE, edge.betweenness = TRUE, merges = TRUE, bridges = TRUE, modularity = TRUE, membership = TRUE)
dend=as.dendrogram(ebc)

png("ebc_dend.png",width=1000,height=800)
par(cex=1,font=3)
plot(dend, main="Title") ##### MODIFY TITLE
dev.off()

### DEGREE DISTRIBUTION CHART ###

degd=degree.distribution(g, cumulative = FALSE) 
degd

png("deg_dist.png",width=1000,height=800)

barplot(degd,xlab="Degree",ylab="Frequency (%)", axes=TRUE, names.arg=(1:#), seq(by=5), axisnames=TRUE, axis.lty=1, cex.names=.85, main="Title") ##### MODIFY THE MAXIMUM DEGREE AND TITLE

dev.off()

### SUMMARY ###

g

### COMPLETE ###