Master R 11 - Social Network analysis of the R Ecosystem

Loading network data

library(tools)

pkgs <- available.packages()

str(pkgs)

head(package.dependencies(pkgs), 2)

library(plyr)

edges <- ldply(

   c('Depends', 'Imports', 'Suggests'), function(depLevel) {

     deps <- package.dependencies(pkgs, depLevel = depLevel)

     ldply(names(deps), function(pkg)

         if (!identical(deps[[pkg]], NA))

             data.frame(

                 src   = pkg,

                 dep   = deps[[pkg]][, 1],

                 label = depLevel,

                 stringsAsFactors = FALSE))

})

str(edges)

Centrality measures of networks

 compute centrality and density metrics

 identify bridges and simulate changes in the network

nrow(edges) / (nrow(pkgs) * (nrow(pkgs) - 1))

head(sort(table(edges$dep), decreasing = TRUE))

edges <- edges[edges$dep != 'R', ]

library(igraph)

g <- graph.data.frame(edges)

summary(g)

graph.density(g)

head(sort(degree(g), decreasing = TRUE))

head(sort(betweenness(g), decreasing = TRUE))

Visualizing network data

plot(degree(g), betweenness(g), type = 'n', main = 'Centrality of R package dependencies')

text(degree(g), betweenness(g), labels = V(g)$name)

edges <- edges[edges$label != 'Suggests', ]

deptree <- edges$dep[edges$src == 'igraph']

while (!all(edges$dep[edges$src %in% deptree] %in% deptree))

   deptree <- union(deptree, edges$dep[edges$src %in% deptree])

deptree

g <- graph.data.frame(edges[edges$src %in% c('igraph', deptree), ])

plot(g)

V(g)$label.color <- 'orange'

V(g)$label.color[V(g)$name == 'igraph'] <- 'darkred'

V(g)$label.color[V(g)$name %in% edges$dep[edges$src == 'igraph']] <- 'orangered'

E(g)$color <- c('blue', 'green')[factor(df$label)]

plot(g, vertex.shape = 'none', edge.label = NA)

tkplot(g, edge.label = NA)

library(visNetwork)

nodes <- get.data.frame(g, 'vertices')

names(nodes) <- c('id', 'color')

edges <- get.data.frame(g)

visNetwork(nodes, edges)

Custom plot layouts

g <- dominator.tree(g, root = "igraph")$domtree

plot(g, layout = layout.reingold.tilford(g, root = "igraph"), vertex.shape = 'none')

Analyzing R package dependencies with an R package

library(miniCRAN)

pkgs <- pkgAvail()

pkgDep('igraph', availPkgs = pkgs, suggests = FALSE, includeBasePkgs = TRUE)

plot(makeDepGraph('igraph', pkgs, suggests = FALSE, includeBasePkgs = TRUE))