Opinion dynamics beyond social influence

被引:0
|
作者
Meylahn, Benedikt, V [1 ]
Searle, Christa [2 ,3 ]
机构
[1] Univ Amsterdam, Korteweg de Vries Inst Math, Amsterdam, Netherlands
[2] Heriot Watt Univ, Edinburgh Business Sch, Edinburgh, Scotland
[3] Stellenbosch Univ, Dept Ind Engn, Stellenbosch Unit Operat Res Engn, Stellenbosch, South Africa
关键词
Opinion dynamics; multi-agent learning; social influence; agent-based simulation; opinion polarisation; Social network dynamics; consensus formation; MAJORITY DYNAMICS; CONVERGENCE; DIFFUSION; TUTORIAL; NETWORKS; MODELS; TRUST;
D O I
10.1017/nws.2024.14
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
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.
引用
收藏
页数:27
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