NETWORK Procedure

This example uses the same data as in Influence Centrality for Project Groups in a Research Department, which illustrates influence centrality by considering the link weights that represent some measure of reporting magnitude. In Example 2.2, links between managers (or leads) and direct reports have higher link weights than links between nonmanagers. This interpretation makes sense in the context of influence centrality because weight and the metric are directly related. However, for closeness and betweenness centrality, weight and the metric are inversely related.

This example considers the speed of the flow of information between people. In this sense, connections between managers and direct reports have smaller values, which cost less in the shortest path calculations. As described in the section Closeness Centrality, by default, PROC NETWORK uses the reciprocal of the link weight to find the shortest paths of the closeness and betweenness centrality metrics.

The following statements calculate weighted (and unweighted) closeness and betweenness centrality.

proc network
   logLevel    = moderate
   links       = mylib.LinkSetInDept
   outLinks    = mylib.LinkSetOut
   outNodes    = mylib.NodeSetOut;
   centrality
      close    = both
      between  = both;
run;
%put &_NETWORK_;

The progress of the procedure is shown in Output 2.4.1.

The nodes data table mylib.NodeSetOut shows the weighted and unweighted closeness and node betweenness centrality, as shown in Output 2.4.2.

The links data table mylib.LinkSetOut shows the weighted and unweighted link betweenness centrality, as shown in Output 2.4.3.

Note that Chapman (the director) and Yu (a manager who reports to Chapman) both have the highest weighted closeness centrality. However, Yu’s weighted betweenness centrality is highest because he serves as a gatekeeper between his three groups (D4a, D4b, and D4c) and the rest of the department.