WHEN INTUITION FAILS: THE COMPLEX EFFECTS OF ASSIMILATIVE AND REPULSIVE INFLUENCE ON OPINION POLARIZATION

Shuo Liu (), Michael Mã„s, Haoxiang Xia () and Andreas Flache ()
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Shuo Liu: School of Economics and Management, Dalian University of Technology, No. 2 Linggong Road, Dalian 116024, P. R. China
Michael Mã„s: Institute of Technology Futures, Karlsruhe Institute of Technology, Douglasstraße 24, Karlsruhe 76133, Germany
Haoxiang Xia: School of Economics and Management, Dalian University of Technology, No. 2 Linggong Road, Dalian 116024, P. R. China
Andreas Flache: Department of Sociology, University of Groningen, Grote Rozenstraat 31, Groningen 9712 TG, The Netherlands

Advances in Complex Systems (ACS), 2022, vol. 25, issue 08, 1-30

Abstract: There is a public and scholarly debate about whether personalized services of social-media platforms contribute to the rise of bipolarization of political opinions. On the one hand, it is argued that personalized services of online social networks generate filter bubbles limiting contact between users who disagree. This reduces opportunities for assimilative social influence between users from different camps and prevents opinion convergence. On the other hand, empirical research also indicated that exposing users to content from the opposite political spectrum can activate the counter-part of assimilative influence, repulsive influence. Fostering contact that leads to opinion assimilation and limiting contacts likely to induce repulsive interactions, it has been concluded, may therefore prevent bipolarization. With an agent-based model, we demonstrate here that these conclusions fail to capture the complexity that assimilative and repulsive influence generate in social networks. Sometimes, more assimilative influence can actually lead to more and not less opinion bipolarization. Likewise, increasing the exposure of users to like-minded individuals sometimes intensifies opinion polarization. While emerging only in specific parts of the parameter space, these counter-intuitive dynamics are robust, as our simulation experiments demonstrate. We discuss implications for the debate about filter bubbles and approaches to improve the design of online social networks. While we applaud the growing empirical research on the micro-processes of assimilative and repulsive influence in online settings, we warn that drawing conclusions about resulting macro-outcomes like opinion bipolarization requires a rigorous analysis capturing the complexity of online communication systems. Intuition alone is error-prone in this context. Accordingly, models capturing the complexity of social influence in networks should play a more important role in the design of communication systems.

Keywords: Opinion polarization; opinion dynamics; repulsion; negative influence; online social networks; filter bubbles; complexity (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0219525922500114

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