On the Complexity of the Bipartite Polarization Problem: from Neutral to Highly Polarized Discussions

TL;DR

This paper explores the complexity of the Bipartite Polarization Problem, showing that higher polarization levels in generated instances correlate with easier solutions, extending understanding of polarization in social network debates.

Contribution

Introduces a new instance generation model linking polarization levels to problem complexity, providing insights into the problem's computational difficulty.

Findings

Higher polarization leads to easier problem instances

Real-world instances from Reddit are generally easy to solve

The model effectively controls polarization and complexity correlation

Abstract

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.