Cocitation coupling
edge.betweenness.community
Community structure detection based on edge betweenness
Plot graphs and their cohesive block hierarchy
Kleinberg's centrality scores.
K-core decomposition of graphs
Method for structural manipulation of graphs
Plotting of graphs
Shortest (directed or undirected) paths between vertices
3D plotting of graphs with OpenGL
Creating igraph graphs from data frames
Geometric random graphs
Subgraph of a graph
Diameter of a graph
ARPACK eigenvector calculation
Graph motifs
The igraph package
The Page Rank algorithm
Find Bonacich Power Centrality Scores of Network Positions
Biconnected components
Connected components of a graph
Permute the vertices of a graph
Simple graphs
Convert a general graph into a forest
Graph Isomorphism
Maximum flow in a network
Line graph of a graph
label.propagation.community
Finding communities based on propagating labels
Topological sorting of vertices in a graph
Convert between directed and undirected graphs
Create a bipartite graph
Creating a graph from LCF notation
Articulation points of a graph
Independent vertex sets
Calculate Cohesive Blocks
The functions find cliques, ie. complete subgraphs in a graph
Canonical permutation of a graph
Print graphs to the terminal
Various methods for creating graphs
Gaining information about graph structure
Graph, vertex and edge attributes
Rewires the endpoints of the edges of a graph randomly
Find the multiple or loop edges in a graph
Interactive plotting of graphs
Writing the graph to a file in some format
Modularity of a community structure of a graph
Transitivity of a graph
Triad census, subgraphs with three vertices
Adjacency lists
Find mutual edges in a directed graph
Neighborhood of graph vertices
Edge connectivity.
Graph density
Graph rewiring
Community structure via greedy optimization of modularity
Strength or weighted vertex degree
Growing random graph generation
Finding communities in graphs based on statistical meachanics
Generate scale-free graphs according to the Barabasi-Albert
model
Vertex connectivity.
Degree and degree distribution of the vertices
In- or out- component of a vertex
Graphs from adjacency lists
Create graphs from adjacency lists
Generate random graphs according to the Erdos-Renyi model
Generate coordinates to place the vertices of a graph in a
star-shape
De Bruijn graphs.
Reciprocity of graphs
Common functions supporting community detection algorithms
Drawing graphs
The Watts-Strogatz small-world model
Creating (small) graphs via a simple interface
Graph generation based on different vertex types
Closeness centrality of vertices
Burt's constraint
Convert a graph to an adjacency matrix or an edge list
Creating named graphs
Create graphs from an incidence matrix
Kautz graphs
Decide whether a graph is bipartite
Generate coordinates for plotting graphs
The DrL graph layout generator
Girth of a graph
Average nearest neighbor degree
igraph from/to graphNEL conversion
Convert igraph graphs to graphNEL objects or back
Similarity measures of two vertices
Generate an evolving random graph with preferential attachment
and aging
Dyad census of a graph
Graph Laplacian
Merging graph layouts
Graph operators
Experimental basic igraph GUI
Running mean of a time series
Community strucure via short random walks
Number of automorphisms
Vertex and edge sequences and iterators
Generate random graphs with a given degree sequence
Various vertex shapes when plotting igraph graphs
Project a bipartite graph
Decompose a graph into components
Find Bonacich alpha centrality scores of network positions
Find Eigenvector Centrality Scores of Network Positions
Create a full bipartite graph
Parameters for the igraph package
Is this object a graph?
Write graphs and their cohesive block hierarchy as Pajek files
Forest Fire Network Model
Load a graph from the graph database for testing graph
isomorphism.
Sampling a random integer sequence
Trait-based random generation
Reading foreign file formats
Create graphs from adjacency matrices
Vertex and edge betweenness centrality
Incidence matrix of a bipartite graph
leading.eigenvector.community
Community structure detecting based on the leading eigenvector
of the community matrix
Minimum spanning tree
Fitting a power-law distribution function to discrete data
conversion between igraph and graphNEL graphs
Convert igraph graphs to graphNEL objects or back