Emergence of Polarized Ideological Opinions in Multidimensional Topic Spaces

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 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 nonorthogonal basis. Opinions evolve according to the social interactions among the agents, which are ruled by homophily: Two agents sharing similar opinions are more likely to interact. The model features phase transitions between a global consensus, opinion polarization, and ideological states. Interestingly, the ideological phase emerges by relaxing the assumption of an orthogonal basis of the topic space, i.e., if topics thematically overlap. Furthermore, we analytically and numerically show that these transitions are driven by the controversialness of the topics discussed; the more controversial the topics, the more likely are opinions to be correlated. Our findings shed light upon the mechanisms driving the emergence of ideology in the formation of opinions.

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Plain Language Summary

Public opinion polarization is on the rise, as suggested by data collected across a variety of political and ethical issues. In the U.S., for example, society recently split with respect to so-called bathroom bills, which restrict public restroom access by gender assigned at birth. Opinions on different topics can also be correlated: Individuals advocating rights for transgender people, for example, are likely to also support same-sex couples. Strikingly, data show correlations between unrelated topics, such as rights of transgender people and the debate about whether the U.S. should build a wall at the border with Mexico. Here, we propose a simple model that reproduces such polarized ideological states, in which opinions are extreme and correlated with respect to different topics.

We develop a mathematical formalism in which opinions evolve in a multidimensional space, representing the relation between different topics. We show that a simple reinforcement mechanism coupled with homophilic social interactions leads to the emergence of polarized, ideological opinions, even between unrelated topics that are sufficiently controversial.

People usually influence each other while discussing a certain topic. But when topics are controversial, the reinforcement mechanism proposed here spills over into a plethora of different topics. Two users advocating for transgender rights in a Twitter debate, for example, will reinforce their stances with respect to other controversial topics, such as the U.S. building a wall at the border with Mexico.

Our findings shed light on the mechanisms—both offline and online—driving the process of opinion formation.