Degree of a node is the number of edges that connect it to other nodes; see Figure 4, degree can be interpreted as measure of power or importance of a node, or measure of workload. The actor with most ties is the most important figure in a network. In a simple random graph, degree will have a Poisson distribution [2], and the nodes with high degree are likely to be at the intuitive center. Deviations from a Poisson distribution suggest non-random processes, which is at the heart of current "scale-free" work on networks. Definition: A graph G, is a collection of nodes N and edges E; G = 1= ,eE}. Definition: Node degree; denoted Ca(n), is defined by Ca(ni) = d(ni) = Σaiji dij € A, j where d represents degree measure, and A is the adjacency matrix. {N, E}, where (1) To illustrate the degree measure, we calculate the node degree for the nodes in Figure 4. The table below shows the results. On the other hand, closeness is based on the inverse of the distance of each actor to every other actor in the network. If an actor is close to all other actors then this actor is considered important. where c represents closeness, d(n,, n,) is the shortest distance between node i and node j. For example, the network in Figure 4 has the following closeness measures: (2) Let us apply the centrality measures to Wegman's network, Figure 9 shows a table of centrality measures. In terms of degree (a local measure), aside from Wegman, which is the most central person in the network simply because he wrote with every member of the network; thus he has the highest degree since he is connected to all other nodes, Solka with normalized node degree of 25.743 comes in second place, he is an important figure because he is the actor with most ties. The third place is shared by Marchette and Priebe with normalized node degree of 15.842. Using closeness metric, Wegman comes in first place, he is the most central person. Solka again has the second highest closeness with a normalized value of 57.386, he is considered important because he is relatively close to all other actors. And finally, Marchette and Priebe |