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Small World Graphs. Amber Rice. Defining a Small World Graph. Relatively HIGH Clustering Coefficient Relatively LOW Characteristic Path Length. Clustering Coefficient. Measure of degree to which vertices in a graph tend to cluster together
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Small World Graphs Amber Rice
Defining a Small World Graph • Relatively HIGH Clustering Coefficient • Relatively LOW Characteristic Path Length
Clustering Coefficient • Measure of degree to which vertices in a graph tend to cluster together • If A is connected to B and B is connected to C, then there’s a heightened probability that A is connected to C.
Clustering Coefficient • C = • Where: • “triangles” are K graphs • “connected triples” are nonisomorphic paths of length two 3
Finding Clustering Coefficient One Triangle 8 Connected Triples So the Clustering Coefficient is 3/8.
Characteristic Path Length • The average number of “steps” along the shortest paths for all possible pairs of vertices in the graph • The median of the means of shortest distances between all pairs of vertices
Finding Characteristic Path Length First, find the distances between all the vertices and each average length. A – 1, 1, 2, 2 mean(A) = 6/4 B – 1, 1, 2, 2 mean(B) = 6/4 C – 1, 1, 1, 1 mean(C) = 4/4 D – 1, 2, 2, 2 mean(D) = 7/4 E – 1, 2, 2, 2 mean(E) = 7/4 Next, take the median of the averages. Median ( 4/4, 6/4, 6/4, 7/4, 7/4 ) = 6/4 A D C E B So, the Characteristic Path Length of this graph is 6/4.
Conclusions • New topic • Not much information • Likely to be very important in the future • My honors project • Social networks on campus
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