An approach from statistical mechanics for collaborative business social network reconstruction

Abstract

The role of human resources has become a key factor for the success of an organization. Based on a research collaboration with an aeronautical company, the paper proposes a comparison of two different approaches for the reconstruction of a collaborative social network in the business realm: the use of traditional Social Network Analysis and novel statistical inference models. Both approaches were evaluated against data provided by the company, in order to scout the key people in the network and the knowledge-transfer processes. As a main outcome of this paper, it was found how the network reconstruction using statistical models has an increased robustness, as well as sensitivity, allowing to discover hidden correlations among the users.