  Multiple countries have recently experienced extreme political polarization,
which in some cases led to escalation of hate crime, violence and political
instability. Beside the much discussed presidential elections in the United
States and France, Britain's Brexit vote and Turkish constitutional referendum,
showed signs of extreme polarization. Among the countries affected, Ukraine
faced some of the gravest consequences. In an attempt to understand the
mechanisms of these phenomena, we here combine social media analysis with
agent-based modeling of opinion dynamics, targeting Ukraine's crisis of 2014.
We use Twitter data to quantify changes in the opinion divide and parameterize
an extended Bounded-Confidence XY Model, which provides a spatiotemporal
description of the polarization dynamics. We demonstrate that the level of
emotional intensity is a major driving force for polarization that can lead to
a spontaneous onset of collective behavior at a certain degree of homophily and
conformity. We find that the critical level of emotional intensity corresponds
to a polarization transition, marked by a sudden increase in the degree of
involvement and in the opinion bimodality.
