A Hybrid Opinion Formation and Polarization Model.

IF 2
Baizhong Yang, Quan Yu, Yi Fan
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Abstract

The last decade has witnessed a great number of opinion formation models that depict the evolution of opinions within a social group and make predictions about the evolution process. In the traditional formulation of opinion evolution such as the DeGroot model, an agent's opinion is represented as a real number and updated by taking a weighted average of its neighbour's opinions. In this paper, we adopt a hybrid representation of opinions that integrate both the discrete and continuous nature of an opinion. Basically, an agent has a 'Yes', 'Neutral' or 'No' opinion on some issues of interest and associates with its Yes opinion a support degree which captures how strongly it supports the opinion. With such a rich representation, not only can we study the evolution of opinion but also that of support degree. After all, an agent's opinion can stay the same but become more or less supportive of it. Changes in the support degree are progressive in nature and only a sufficient accumulation of such a progressive change will result in a change of opinion say from Yes to No. Hence, in our formulation, after an agent interacts with another, its support degree is either strengthened or weakened by a predefined amount and a change of opinion may occur as a consequence of such progressive changes. We carry out simulations to evaluate the impacts of key model parameters including (1) the number of agents, (2) the distribution of initial support degrees and (3) the amount of change of support degree changes in a single interaction. Last but not least, we present several extensions to the hybrid and progressive model which lead to opinion polarization.

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一种混合意见形成与极化模型。
在过去的十年中,出现了大量的意见形成模型,这些模型描述了社会群体内部意见的演变,并对演变过程进行了预测。在DeGroot模型等传统的意见演变公式中,代理的意见被表示为实数,并通过对其邻居的意见进行加权平均来更新。在本文中,我们采用了一种混合的意见表示,它结合了意见的离散性和连续性。基本上,一个代理在某些感兴趣的问题上有“是”、“中立”或“否”的意见,并将其“是”意见与一个支持度联系起来,该支持度反映了它对该意见的支持程度。有了这样丰富的代表性,我们不仅可以研究意见的演变,而且可以研究支持度的演变。毕竟,代理人的意见可以保持不变,但会变得或多或少地支持它。支持度的变化是渐进式的,只有这种渐进式变化的积累足够多,才会导致观点从“是”变为“否”。因此,在我们的表述中,一个代理与另一个代理相互作用后,其支持度会以预定义的量增强或减弱,并且这种渐进变化可能会导致意见的变化。我们进行了模拟来评估关键模型参数的影响,包括(1)智能体的数量,(2)初始支持度的分布,(3)单个交互中支持度变化的变化量。最后但并非最不重要的是,我们提出了导致意见两极分化的混合和渐进模型的几个扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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