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Role of propagation thresholds in sentiment-based model of opinion evolution with information diffusion

机译:传播阈值在带有信息扩散的基于情感的观点演化模型中的作用

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The degree of sentiment is the key factor for internet users in determining their propagating behaviors, i.e. whether participating in a discussion and whether withdrawing from a discussion. For this end, we introduce two sentiment-based propagation thresholds (i.e. infected threshold and refractory threshold) and propose an interacting model based on the Bayesian updating rules. Our model describe the phenomena that few internet users change their decisions and that someone has drop out of discussion about the topic when some others are just aware of it. Numerical simulations show that, large infected threshold restrains information diffusion but favors the lessening of extremism, while large refractory threshold facilitates decision interaction but promotes the extremism. Making netizens calm down and propagate information sanely can restrain the prevailing of extremism about rumors. (C) 2016 Elsevier B.V. All rights reserved.
机译:情感程度是互联网用户确定其传播行为(即是否参与讨论以及是否退出讨论)的关键因素。为此,我们引入了两个基于情感的传播阈值(即感染阈值和难治性阈值),并提出了一个基于贝叶斯更新规则的交互模型。我们的模型描述了以下现象:很少有互联网用户会更改他们的决定,而当其他人只是意识到这一点时,就会有人放弃对该主题的讨论。数值模拟表明,较大的感染阈值抑制信息扩散,但有利于减少极端主义,而较大的不应阈值则有利于决策交互,但可以促进极端主义。使网民冷静下来并理性地传播信息可以抑制有关谣言的极端主义的盛行。 (C)2016 Elsevier B.V.保留所有权利。

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