Analysing websites internal linking is key to understand their architecture of information and web structure and thus their potential of Search Engine Optimization, SEO.

Graphs are made of nodes and edges. In SEO nodes are webpages and edges, links directed to them from other webpages on the graph.

library(igraph) dat=read.csv(file.choose(),header=TRUE) # choose an edgelist in .csv file format g=graph.data.frame(dat,directed=TRUE) transitivity(g)

Transitivity or clustering coefficient is the probability that the adjacent vertices of a vertex are connected.

Count vertices vcount(graph)

Count edges ecount(graph)

Diameter

diameter(graph)

The diameter of a graph is the length of the longest geodesic.

Graph density

graph.density(graph)

The density of a graph is the ratio of the number of edges and the number of possible edges.