Opinion dynamics beyond social influence

Benedikt V. Meylahn*, Christa Searle

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

We present an opinion dynamics model framework discarding two common assumptions in the literature: (a) that there is direct influence between beliefs of neighboring agents, and (b) that agent belief is static in the absence of social influence. Agents in our framework learn from random experiences which possibly reinforce their belief. Agents determine whether they switch opinions by comparing their belief to a threshold. Subsequently, influence of an alter on an ego is not direct incorporation of the alter’s belief into the ego’s but by adjusting the ego’s decision-making criteria. We provide an instance from the framework in which social influence between agents generalizes majority rules updating. We conduct a sensitivity analysis as well as a pair of experiments concerning heterogeneous population parameters. We conclude that the framework is capable of producing consensus, polarization and fragmentation with only assimilative forces between agents which typically, in other models, lead exclusively to consensus.
Original languageEnglish
Pages (from-to)339-365
Number of pages27
JournalNetwork Science
Volume12
Issue number4
Early online date21 Oct 2024
DOIs
Publication statusPublished - Dec 2024

Keywords

  • Opinion dynamics
  • multi-agent learning
  • social influence
  • agent-based simulation
  • opinion polarisation
  • Social network dynamics
  • consensus formation

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