The digital age has seen an exponential increase in the creation and dissemination of information, while the post-truth era has amplified the role of emotion in the spread of news. To prevent the outbreak of negative public sentiment due to uncontrolled emotional responses, it is critical to investigate the interplay between these two factors during the propagation. Therefore, we develop an emotion-information multiplex network based on the topic discussion function of social media. According to the influence of emotion on information transmission, emotion is divided into positive, negative and uninterested which are introduced into the standard SIR model. The microscopic Markov chain approach (MMCA) is used to analyze the outbreak threshold proving that emotion affects the threshold of information propagation. The extensive Monte Carlo (MC) simulations show that the average degree of information layer affects the emotional atmosphere. Secondly, the rapid dissemination of information will widen the emotional differences between people. Finally, positive or uninterested can easily become the dominant emotion of the group, and the group effect is more easily reflected in the user’s supportive attitude rather than the opposition attitude.

中文翻译：

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多重网络上社交媒体的情感信息传播模型


数字时代信息的创造和传播呈指数级增长，而后真相时代则放大了情感在新闻传播中的作用。为了防止因情绪反应失控而引发负面公众情绪，研究这两个因素在传播过程中的相互作用至关重要。因此，我们开发了一个基于社交媒体话题讨论功能的情感信息复用网络。根据情绪对信息传递的影响，将情绪分为积极情绪、消极情绪和无兴趣情绪，并将其引入标准SIR模型中。采用微观马尔可夫链方法（MMCA）分析爆发阈值，证明情绪影响信息传播阈值。广泛的蒙特卡罗（MC）模拟表明，信息层的平均程度影响情绪氛围。其次，信息的快速传播会拉大人与人之间的情感差异。最后，积极或不感兴趣很容易成为群体的主导情绪，群体效应更容易体现在用户的支持态度而不是反对态度上。