  Studying and understanding social networks is crucial for accurately defining
ideological polarization, since they enable precise modeling of social
structures. One of the limitations of many methods for quantifying polarization
on networks is the assumption of a two-dimensional opinion space. This prevents
accurate study of multipolar systems like multi-party political systems, where
modeling more than two opinion poles is beneficial. Here, I experimentally
compare methods for quantifying multipolar polarization on a network, and find
that the average pairwise distance extension of generalized Euclidean distance
conforms to several desired properties, showing its advantages over other
methods. This allows study of multipolar polarized systems based on an
empirically and intuitively good metric.
