9515434 Skvoretz The proposed research is a cooperative effort between researchers at the University of Carolina (John Skvoretz and David Willer) and the University of Iowa (Michael Lovaglia and Barry Markovsky). This work extends a program of theory-based investigations on power and social exchange processes. Network Exchange Theory (NET) is one of several theories that attempt to explain the development of power in networks of exchange relations. While previous research has demonstrated that NET predictions are more accurate than its competitors, a problem recently surfaced in a fundamental part of the theory that classifies networks as strong or weak power, the Graph-theoretical Power Index (GPI). In solving this problem, two independent methods of predicting power relations in exchange networks were developed by the investigators. This set the stage for a dramatic improvement in the sped and quality of exchange research. By developing integrated computer programs, the investigators proposed to automate the systematic construction, comparison and classification of exchange networks. Networks for which the two methods disagree can be culled from further analysis from thousands of potential test networks. This will then enable the PIs to make exact predictions for resource distribution in these networks and compare them to computer simulations. The entire process of discovering problematic test networks and preparing them for experimental test can be accomplished in a matter of hours, whereas previously, suitable test networks were discovered largely by chance and the process could take years. Then the PIs propose to improve experimental methods and statistical techniques to investigate a number of networks that were crucial in the solution to the classification problem. These advances will bring us a step closer to modeling exchange processes in complex networks commonly found in society. ***
