Active influence in dynamical models of structural balance in social networks

TL;DR

This paper studies how individual agents in a social network can actively influence the overall structure of the network by perturbing their own friendliness levels, demonstrating controllability of social balance states.

Contribution

It introduces a method for agents to achieve desired social balance states through local influence and proposes a new centrality measure for signed networks.

Findings

Any agent can steer the network to any balanced state via local perturbations.

A new centrality measure for signed networks is proposed.

Empirical validation using United Nations voting data from 1946 to 2008.

Abstract

We consider a nonlinear dynamical system on a signed graph, which can be interpreted as a mathematical model of social networks in which the links can have both positive and negative connotations. In accordance with a concept from social psychology called structural balance, the negative links play a key role in both the structure and dynamics of the network. Recent research has shown that in a nonlinear dynamical system modeling the time evolution of "friendliness levels" in the network, two opposing factions emerge from almost any initial condition. Here we study active external influence in this dynamical model and show that any agent in the network can achieve any desired structurally balanced state from any initial condition by perturbing its own local friendliness levels. Based on this result, we also introduce a new network centrality measure for signed networks. The results are illustrated in an international relations network using United Nations voting record data from 1946 to 2008 to estimate friendliness levels amongst various countries.