Towards distribution-based control of social networks

Abstract

BackgroundComplex networks are found in many domains and the control of these networks is a research topic that continues to draw increasing attention. This paper proposes a method of network control that attempts to maintain a specified target distribution of the network state. In contrast to many existing network control research works, which focus exclusively on structural analysis of the network, this paper also accounts for user actions/behaviours within the network control problem.MethodsThis paper proposes and makes use of a novel distribution-based control method. The control approach is applied within a simulation of the real-valued voter model, which could have applications in problems such as the avoidance of consensus or extremism. The network control problem under consideration is investigated using various theoretical network types, including scale free, random, and small world.ResultsIt is argued that a distribution-based control approach may be more appropriate for several types of social control problems, in which the exact state of the system is of less interest than the overall system behaviour. The preliminary results presented in this paper demonstrate that a standard reinforcement learning approach is capable of learning a control signal selection policy to prevent the network state distribution from straying far from a specified target distribution.ConclusionsIn summary, the results presented in this paper demonstrate the feasibility of a distribution-based control solution within the simulated problem. Additionally, several interesting questions arise from these results and are discussed as potential future work.

Determination of Subjects’ Significance Rate and Optimal Information Control in Social Networks

“…are not equivalent problems, although both of these one-criterion problems are generated by the same original problem (2) of vector unconditional optimization, and are different ways to solve (2) by reducing it to a one-criterion problem: we insist that the problem ( 3) is more preferable because of its scientifically based derivation from (2) (see: Coello Coello, Lamont, & van Veldhuizen, 2007;Steuer, 1986;Keeney & Raiffa, 1993;Gembicki, 1973). Now let us discuss three of the many possible objectives of a network control/governing body (for instance, see Gubanov et al, 2010;Volodenkov, 2015;McKenney & White, 2018;Goyal, Karamchandani, Chatterjee, & Manjunath, 2019): (A) the objective of neutralizing the actions of network subjects; (B) the objective of a softly regulated weakening of the actions of network subjects; (C) the purpose of a softly regulated strengthening of the actions of network subjects.…”