The Bipartite Polarization Problem is an optimization problem where the goal
is to find the highest polarized bipartition on a weighted and labelled graph
that represents a debate developed through some social network, where nodes
represent user's opinions and edges agreement or disagreement between users.
This problem can be seen as a generalization of the maxcut problem, and in
previous work approximate solutions and exact solutions have been obtained for
real instances obtained from Reddit discussions, showing that such real
instances seem to be very easy to solve. In this paper, we investigate further
the complexity of this problem, by introducing an instance generation model
where a single parameter controls the polarization of the instances in such a
way that this correlates with the average complexity to solve those instances.
The average complexity results we obtain are consistent with our hypothesis:
the higher the polarization of the instance, the easier is to find the
corresponding polarized bipartition.

通过引入一种实例生成模型，研究了双向极化问题的复杂性，结果表明，实例的极化程度越高，找到对应的极化二分图越容易。