Emergence of polarized ideological opinions in multidimensional topic spaces
Fabian Baumann, Philipp Lorenz-Spreen, Igor M. Sokolov, Michele, Starnini

TL;DR
This paper introduces a multidimensional opinion model demonstrating how ideological polarization and correlated opinions can emerge from social interactions and topic overlaps without preexisting assumptions, highlighting the role of controversy.
Contribution
The study presents a formal model of opinion dynamics in non-orthogonal topic spaces, revealing phase transitions and the impact of controversy on opinion correlation.
Findings
Ideological states emerge from overlapping topics.
Controversial topics increase opinion correlation.
Model reproduces survey data patterns.
Abstract
Opinion polarization is on the rise, causing concerns for the openness of public debates. Additionally, extreme opinions on different topics often show significant correlations. The dynamics leading to these polarized ideological opinions pose a challenge: How can such correlations emerge, without assuming them a priori in the individual preferences or in a preexisting social structure? Here we propose a simple model that qualitatively reproduces ideological opinion states found in survey data, even between rather unrelated, but sufficiently controversial, topics. Inspired by skew coordinate systems recently proposed in natural language processing models, we solidify these intuitions in a formalism of opinions unfolding in a multidimensional space where topics form a non-orthogonal basis. Opinions evolve according to the social interactions among the agents, which are ruled by…
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