2023/05/16 by Benedikt V. Meylahn, Meylahn, Benedikt V., Christa Searle +1
Physics and Astronomy · #91D30 #Complex Network Analysis Techniques #FOS: Mathematics #FOS: Physical sciences #Opinion Dynamics and Social Influence #Optimization and Control (math.OC) #Physics and Society (physics.soc-ph)
paper · pdf · doi:10.48550/arxiv.2305.09398
openalex publication_date 2023/05/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
We present an opinion dynamics model framework discarding two common assumptions in the literature: (a) that there is direct influence between beliefs of neighbouring 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 generalises 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, polarisation and fragmentation with only assimilative forces between agents which typically, in other models, lead exclusively to consensus.