Identifying Organizational Influentials: Methods and Application using Social Network Data

Uncovering the most influential individuals in an organization may be of great use for researchers and practitioners. As central hubs in the organization, these individuals can be key co-creators or co-adapters for the diffusion of organizational reform. In this paper we examine the question “Who are the most influential individuals in an organization?” Using social network data, we assess organizational members’ levels of influence in four different advice-seeking networks, as well as in one “friendship” network through a measure of peer-endorsement. We investigate four methods for the classification of individuals as “influentials”. These methods are compared and contrasted according to their performance in handling problems of differing network sizes, densities, non-response rates, researcher decisions and parsimony. A nonparametric random permutation method is shown to be a consistent and objective process for the identification of influential individuals in a sample of High school staff members in nine schools.