Opinion formation in an adaptive social networks

Abstract

Opinion formation in adaptive social networks is a fascinating topic in the area of network science and social dynamics. The purpose of this report is to investigate the process of opinion diversity and to analyse the dynamic evolution relationship between the network structure and opinions, revealing the inherent law behind them. Computer simulation, theoretical modeling, and analysis are employed to construct a simulation model that depicts real-world scenarios of opinion propagation on complex networks. The Deffuant-Weisbuch model is utilized to generate the output. The model output suggests the emergence of intricate system dynamics. that ultimately propels the system into a state of dynamic equilibrium while also allowing the coexistence of diverse opinions. By feeding the model with various experimental values and forming propositions we have discovered that when in equilibrium, non-trivial connections persist instead of creating disconnected social groups and therefore allowing interactions and change of opinions to occur easily. Moreover, with different tolerance levels set, we can also observe different groups of communities that are in a steady state. Overall, the analytical findings align well with the results obtained from the simulation.