Opinion fluctuations and disagreement in social networks

Computer Science – Social and Information Networks

Scientific paper

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27 pages, submitted to Mathematics of Operation Research, revised

Scientific paper

We study an inhomogeneous stochastic gossip process of continuous opinion dynamics in a society consisting of two types of agents: regular agents, who update their beliefs according to information that they receive from their social neighbors; and stubborn agents, who never update their opinions and might represent leaders, political parties or media sources attempting to influence the beliefs in the rest of the society. When the society contains stubborn agents with different opinions, the belief dynamics never lead to a consensus. Instead, beliefs in the society almost surely fail to converge, the belief profile keeps on oscillating in an ergodic fashion, and it converges in law to a non-degenerate random vector. The expected belief vector is proved to evolve according to an ordinary differential equation coinciding with the Kolmogorov backward equation of a continuos time Markov chain on the graph with absorbing states corresponding to the stubborn agents, and hence to converge to a harmonic vector, with every regular agent's value being the weighted average of its neighbors' values, and boundary conditions corresponding to the stubborn agents' beliefs.It is proved that, in large-scale societies which are `highly fluid', meaning that the product of the mixing time of the random walk on the graph describing the social network and the relative size of the linkages to stubborn agents vanishes as the population size grows large, a condition of `homogeneous influence' emerges, whereby the stationary beliefs' marginal distributions of most of the regular agents have approximately equal first and second moment. Homogeneous influence in a highly fluid societies need not imply approximate consensus among the agents, whose beliefs may well oscillate in an essentially uncorrelated way.

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