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阿克塞尔罗德文化传播模型中的一致性阈值。

Agreement threshold on Axelrod's model of cultural dissemination.

机构信息

Centre for Social Issues Research, University of Limerick, Limerick, Ireland.

Department of Mathematics & Statistics, MACSI (Mathematics Applications Consortium for Science and Industry), University of Limerick, Limerick, Ireland.

出版信息

PLoS One. 2020 Jun 2;15(6):e0233995. doi: 10.1371/journal.pone.0233995. eCollection 2020.

Abstract

Shared opinions are an important feature in the formation of social groups. In this paper, we use the Axelrod model of cultural dissemination to represent opinion-based groups. In the Axelrod model, each agent has a set of features which each holds one of a set of nominally related traits. Survey data has a similar structure, where each participant answers each of a set of items with responses from a fixed list. We present an alternative method of displaying the Axelrod model by representing it as a bipartite graph, i.e., participants and their responses as separate nodes. This allows us to see which feature-trait combinations are selected in the final state. This visualisation is particularly useful when representing survey data as it illustrates the co-evolution of attitudes and opinion-based groups in Axelrod's model of cultural diffusion. We also present a modification to the Axelrod model. A standard finding of the Axelrod model with many features is for all agents to fully agree in one cluster. We introduce an agreement threshold and allow nodes to interact only with those neighbours who are within this threshold (i.e., those with similar opinions) rather than those with any opinion. This method reliably yields a large number of clusters for small agreement thresholds and, importantly, does not limit to single cluster when the number of features grows large. This potentially provides a method for modelling opinion-based groups where as opinions are added, the number of clusters increase.

摘要

共享观点是社会群体形成的一个重要特征。在本文中,我们使用阿克塞尔罗德的文化传播模型来表示基于观点的群体。在阿克塞尔罗德模型中,每个代理都有一组特征,每个特征都包含一组名义上相关的特征。调查数据具有类似的结构,每个参与者用固定列表中的回复回答一组项目中的每一个。我们提出了一种替代的方法来展示 Axelrod 模型,将其表示为二分图,即参与者及其回复作为单独的节点。这使我们能够看到在最终状态中选择了哪些特征-特征组合。这种可视化在表示调查数据时特别有用,因为它说明了态度和基于观点的群体在 Axelrod 的文化扩散模型中的共同演变。我们还对 Axelrod 模型进行了修改。对于具有许多特征的 Axelrod 模型的一个标准发现是,所有代理在一个聚类中完全一致。我们引入了一个一致性阈值,并允许节点仅与那些在该阈值内的邻居(即具有相似观点的邻居)而不是那些具有任何观点的邻居进行交互。当一致性阈值较小时,这种方法可靠地产生大量聚类,并且当特征数量增加时,重要的是不会将聚类限制为单个聚类。这为基于观点的群体建模提供了一种方法,随着观点的增加,聚类的数量会增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c8b/7266322/c5ff461fc75c/pone.0233995.g001.jpg

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