Quantifying the potentiality for polarization in opinion networks

Abstract

Polarization in debates and social networks is a phenomenon clearly present in modern societies that strongly modifies the way we relate as communities. Regardless of the importance of this phenomenon, there is not a clear explanation yet for its emergence or a suitable parameter to quantify it. Here, we present a methodology based on the Turing instability, a frequent mechanism in Nature which explains differentiation processes, that maps the conditions needed for a given network to undergo polarization of opinions. From this mapping, we measure the likelihood of the system's nodes to differentiate each other or, in other terms, the degree of polarization of the network