THE OPTIMIZATION OF THE INFORMATIONAL FLOW IN A SOCIAL NETWORK - A PROTEIN NETWORK-BASED APPROACH

As social beings, human individuals are involved in a complx relational structure; which can be represented as a graph withmany vertices (individuals) and edges (inter-individuals relations). The assurance of a smooth communication stream between any individuals that are part of such a complex social network is an inherently problematic task. This paper introduces an integrated inter-personal communication quality assurance method that is based on the study of protein networks. Proteins and the networks they determine, called interactome networks, have received attention at an important degree during the last years, because they have been discovered to have an influence on some complex biological phenomena, such as problematic disorders like cancer. The method assesses each individual in the social network on two dimensions, considering the analysis of the biological network as a model. Thus, it computes his / her importance, and properly assigns each individual to their socially determined communities. The procedure allows for an informative and comprehensive analysis of social networks to be conducted, at various levels of complexity. The practical performance and usefulness of the quality assurance method was carefully tested on real social data and the results acknowledge it is able to process existing social data sets in a timely and informative manner, considering existing one-processor hardware architectures.