The influence of the connections' density on clusterization and percolation threshold during information distribution in social networks

The paper is focused on applying new theoretical approaches to describing the processes of information transmission and transformation in sociotechnical systems and in social networks based on the percolation theory. Percolation threshold of a random network depends on its density. In networks with random structure, in both the task of bonds and the task of nodes, percolation thresholds reach saturation when the network’s density is high. The saturation value of a percolation threshold is higher in the task of bonds. From the point of information influence of a random network, increasing the average connection’s density within the network turns out to be more preferable than fostering a small number of separate ‘central nodes’ with numerous connections. The results obtained in this study can be applied in interdisciplinary research in such areas as informatics, mathematic modeling, and economics involving certain sociological survey data for forecasting behavior and managing groups of individuals in network communities. This research enhances and enlarges the scope of methods and approaches applied in classic informatics for describing social and sociotechnical systems, which can be useful for a wide range of researchers engaged into studying social network structures.