Closeness Centrality

Closeness Centrality

Closeness Centrality Problems: large for peripheral vertices • i-j path is infinity for different connected components Solution : Harmonic Mean Distance Centrality • In practice C spans relatively small range of values • Highly sensitive (one edge removal and all distances are increased) • Geodesic distances are integers, often small because distance increases logarithmically with the size of the network • Example: Internet Movie Database highest centrality = 0.4143, lowest centrality = 0.1154, ratio 3.6 for 500K actors Introduction to Network Science 13 Closeness Centrality http://geuz.org/gmsh/ Introduction to Network Science 14 Closeness and Degree-based Centralities Example in Gephi: degrees vs eigenvector centrality Some correlation is expected for certain types of networks Introduction to Network Science 15 Enumeration of Shortest Paths-based Centrality is a number of s-t shortest paths containing i is a number of all s-t shortest-paths Observation: In practice, communication or transport of goods in networks follow different kinds of paths that tend to be shortest. Intuitive Question: How much work can be done by a node? Disadvantage? Stress Centrality for nodes for edges Relation between stress centralities Betweenness Centrality Interpretation: BC is a quantification of communication control which has a vertex over all pairs of nodes. Introduction to Network Science 16 Communication Control Quantification: Example from Brandes “Network Analysis” BC for edges Problem BC is very sensitive to network dynamics (edge/node removal/addition) Solution? ε-BC: in BC replace all shortest s-t paths with all shortest paths that are not longer than (1+ε)δij Introduction to Network Science 17 We have to be careful with shortest path-based centralities, example Introduction to Network Science 18 Homework: Prove that in directed graphs the relation between centralities holds Submit by 1/30/2014 Introduction to Network Science 19 Traversal Sets Homework: Prove that G[Tij] is bipartite. Submit by 1/30/2014 |Tij| is an illuminating measure Another measure based on Tij is the edge centrality index that can be used in characterization of networks with hierarchical organization. Note: there is a theorem that says the following: in bipartite graphs the minimum size of a vertex cover = the size of a maximum matching Introduction to Network Science 20 Transportation Roads Density www.newscientist.com Introduction to Network Science 21 .

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