Social networks represent relationships involving social entities such as friendships among individuals, communication in a group, or transactions between corporations. Finding important actors, discovering cohesive groups or communities, or identifying actors that are similar in some way are all examples of analysis that can be done for social networks.
Building on its strong graph capabilities, Mathematica allows you to model and analyze networks in a flexible and powerful way. Social networks are accessible from a variety of sources, including directly from social media (Facebook, Twitter, ...). High-level functions make it easy to detect communities, find cohesive groups, and visualize the results. A full suite of social network measures makes it possible to explore networks, rank actors from their centralities, or provide recommendations based on similar actors.
Graph — represent a graph with actors and links
SocialMediaData — graph data from social sites (Facebook, Twitter, ...)
CommunityGraphPlot — visualize communities in graphs
FindClique — find cliques
FindGraphCommunities — find communities
DegreeCentrality — number of direct links to other actors
ClosenessCentrality — inverse average distance to every other actor
BetweennessCentrality — fraction of shortest paths that pass through the actor
GraphReciprocity — fraction of directed links that are reciprocated
GlobalClusteringCoefficient — fraction of length-two paths that are closed
GraphAssortativity — within-groups connectivity minus between-group connectivity
VertexCorrelationSimilarity — correlation similarity between actors
RandomGraph — construct random graphs from symbolic graph distributions
GraphPropertyDistribution — distribution of a graph property