This uses specialized extensions of sociometrics to take data of the type described above and to position the elements in relation to each other on the basis of various measures of distance, with those most connected tending to be placed at the centre of a network and those least connected at the periphery. The advantage of this approach is that it endeavours to mirror the network on the basis of its internal characteristics. A number of software packages exist to perform the necessary computations. Various ways of describing a network and identifying key components result from such analysis. Few of the packages are designed to permit mapping of the resultant network.
Data is output in matrix form only or as indices in relation to key elements.
Such computations can consume considerable amounts of computer time, even on fast machines. This approach has been explored using test data from the UIA Revelation database consisting of some 5,000 nodes. The work was done on a Mac II using software developed at the University of Dartmouth by Joel Levine of the Department of Mathematical Social Sciences. This would involve positioning the nodes on a grid determined by the subjects with which they are associated. Relationships would then be plotted between the nodes.