The information theoretic entropy function as a total expected participation index for communication network experiments

This paper shows how the concept of an incidence matrix of communications can be used to define the entropy of a finite scheme. The properties of the entropy function are examined and the function is found to be best interpreted as a total expected participation index. Data is presented showing the relationship between structural centrality and the new total expected participation index. In general, as the network becomes more centralized the smaller the value of the participation index and as the network becomes more structurally decentralized the greater the participation index.This research was supported in part by Ford Foundation Grant 1-40055 to the Graduate School of Industrial Administration at Carnegie Institute of Technology for Research in Organizational Behavior.The author wishes to acknowledge the aid of Terry B. Marbach in the preparation of data.