Complex systems models have demonstrated over and over again that disunity (i.e., cultural polarization, geographic segregation, etc.) can emerge in systems within which information flows freely. The lesson is that having a high degree of information flow doesn't guarantee homogeneity at the scale at which the information is flowing. Two simple models demonstrate this point nicely.
First, the Schelling Model. If you're a fan of complex systems theory, you've probably heard of the simple simulation model that Thomas Schelling constructed and explored in the early 1970's and published in Micromotives and Macrobehavior (1978). The original model was implemented using coins and graph paper rather than a computer. It demonstrated how relatively small preferences about the characteristics of ones' neighbors can result in complete segregation of neighborhoods. Actors in the model make decisions about whether to stay put or move based on on information about their immediate surroundings. Through a multitude of individual, localized decisions, large-scale patterns of segregation emerge in the absence of any intent or authoritative control.
And of course there's no such thing as a "simple" complex systems problem. But complex systems theory has helped us understand a thing or two about human cultural/social/political behavior that we wouldn't be able to understand otherwise. And some of that understanding has come from some relatively simple models. I'm sure there has already been work done extending models like Schelling's and Axelrod's to represent media influences, complex structures of interaction (i.e., different network topologies, etc.), variable demography, etc. The smart money will pay attention to that work to help identify and understand the characteristics of our system that exacerbate divisions (and can be used to widen those divisions).