The bio-inspired and social evolution of node and data in a multilayer network

Abstract

Following a bio-inspired approach, applied to multilayer social networks, the idea is to build a novel paradigm aimed to improve methodologies and analysis in the Information and Communication Technologies. The social network and the multilayer structure allow to carry out an analysis of the complex patterns, in terms of the dynamics involving the main entities, nodes and data. The nodes represent the basic kernel from which generating ties, interactions, flow of information, influences and action strategies that affect the communities. The data, gathered from multiple sources, after their integration, will become complex objects, enclosing different kinds of information. The proposed approach introduces a level of abstraction that originates from the evolution of nodes and data transformed in “social objects”. This new paradigm consists of a multilayer social network, divided into three layers, generating an increasing awareness, from “things” to “knowledge”, extracting as much “knowledge” as possible. This paradigm allows to redesign the ICT in a bio-networks driven approach.