Importance of initial conditions in the polarization of complex networks
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Most existing models of opinion formation use random initial conditions. In reality, most people in a social network, except for a small fraction of the population, are initially either unaware of, or indifferent to, the disputed issue. To explore the consequences of such specific initial conditions, we study the polarization of social networks when conflicting ideas arise on two different seed nodes and then spread according to a majority rule. We find that these initial conditions produce considerably different results than those obtained with the random initial conditions. We further show that an underlying community structure and a fat-tailed degree distribution compete with each other to decide whether the network would polarize or not. Our work suggests that the existing opinion dynamics models should be reevaluated to incorporate the initial condition dependence.
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