Calculating the Clustering Coefficient of a friend network
In this example, adapted from Niko Gamulins blog post on Neo4j for Social Network Analysis, the graph in question is showing the 2-hop relationships of a sample person as nodes with KNOWS relationships.
The clustering coefficient of a selected node is defined as the probability that two randomly selected neighbors are connected to each other.
With the number of neighbors as n and the number of mutual connections between the neighbors r the calculation is
the number of possible connections between two neighbors is n!/(2!(n-2)!) = 4!/(2!(4-2)!) = 24/4 = 6, where n is the number of neighbors n = 4 and the actual number r of connections is 1.
Therefore, the clustering coefficient of node 1 is 1/6.
n and r are quite simple to retrieve via the following query:
MATCH (a {name: "startnode"})--(b)
WITH a, count(distinct b) AS n
MATCH (a)--()-[r]-()--(a)
RETURN n, count(distinct r) AS rThis returns n and r for the above calculations.
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