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Modeling and Simulation of Polarization in Internet Group Opinions Based on Cellular Automata

机译:基于元胞自动机的互联网群体意见极化的建模与仿真

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摘要

Hot events on Internet always attract many people who usually form one or several opinion camps through discussion. For the problem of polarization in Internet group opinions, we propose a new model based on Cellular Automata by considering neighbors, opinion leaders, and external influences. Simulation results show the following: (1) It is easy to form the polarization for both continuous opinions and discrete opinions when we only consider neighbors influence, and continuous opinions are more effective in speeding the polarization of group. (2) Coevolution mechanism takes more time to make the system stable, and the global coupling mechanism leads the system to consensus. (3) Opinion leaders play an important role in the development of consensus in Internet group opinions. However, both taking the opinion leaders as zealots and taking some randomly selected individuals as zealots are not conductive to the consensus. (4) Double opinion leaders with consistent opinions will accelerate the formation of group consensus, but the opposite opinions will lead to group polarization. (5) Only small external influences can change the evolutionary direction of Internet group opinions.
机译:互联网上的热门事件总是吸引着很多人,他们通常通过讨论形成一个或几个意见阵营。针对互联网群体意见分歧的问题,我们提出了一种基于元胞自动机的新模型,该模型考虑了邻居,意见领袖和外部影响。仿真结果表明:(1)仅考虑邻居的影响,连续意见和离散意见都容易形成极化,连续意见在加速群体极化方面更有效。 (2)协同进化机制需要花费更多时间来使系统稳定,而全局耦合机制会使系统达到共识。 (3)意见领袖在互联网团体意见共识的发展中起着重要作用。但是,以意见领袖为狂热分子和以一些随机选择的个人为狂热分子都不利于达成共识。 (4)具有一致意见的双重意见领袖会加速小组共识的形成,但相反的意见会导致小组两极化。 (5)只有很小的外部影响才能改变互联网群体意见的演变方向。

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