Revealing the sentiment propagation under the conscious emotional contagion mechanism in the social media ecosystem: For public opinion management

IF 2.7 3区 数学 Q1 MATHEMATICS, APPLIED
Fulian Yin , Xinyi Jiang , Jinxia Wang , Yan Guo , Yuewei Wu , Jianhong Wu
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引用次数: 0

Abstract

In public opinion events, the breeding of negative sentiment has a serious negative impact on the network environment and even offline lives. Hence, establishing an emotion-based propagation dynamic model to catch the sentiment development patterns is essential for helping public opinion management. We propose an E-SLFI (Emotion-driven Susceptible-Latent-Forwarding-Immune) model, which describes the dynamics of the sentiment propagation of ternary polarities under the promoting effect of the conscious emotional contagion mechanism. An empirical case composed of 16,354 pieces of forwarding information and two phases verifies the effectiveness of the proposed sentiment propagation dynamic model, due to the fitting optimization indicator MAPE equals 0.0942 % and 0.0066 % respectively. Further, we simulate the model and implement sensitivity analysis of the important parameters of the model. Combining the results of experiments, we find that enhancing the emotional consensus of recipients and inducers can decide the main sentiment in the system, and anti-emotional consensus can improve the existence of weak sentiments. Our work here is conducive to designing online public sentiment guidance strategies to manage public opinion and calming the network atmosphere to a certain extent.

揭示社交媒体生态系统中有意识情绪传染机制下的情绪传播:用于舆论管理
在舆情事件中,负面情绪的滋生会对网络环境甚至线下生活造成严重的负面影响。因此,建立基于情绪的传播动态模型,捕捉情绪发展规律,对于舆情管理至关重要。我们提出了一个 E-SLFI(情感驱动的易感-滞后-前向-免疫)模型,该模型描述了在有意识的情感传染机制的促进作用下,三元极性的情感传播动态。由 16354 条转发信息和两个阶段组成的实证案例验证了所提出的情感传播动态模型的有效性,拟合优化指标 MAPE 分别等于 0.0942 % 和 0.0066 %。此外,我们还对模型进行了仿真,并对模型的重要参数进行了灵敏度分析。结合实验结果,我们发现增强收信人和发信人的情感共识可以决定系统中的主要情感,而反情感共识则可以改善弱情感的存在。我们的工作有利于设计网络舆情引导策略来管理舆情,并在一定程度上缓和网络气氛。
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来源期刊
Physica D: Nonlinear Phenomena
Physica D: Nonlinear Phenomena 物理-物理:数学物理
CiteScore
7.30
自引率
7.50%
发文量
213
审稿时长
65 days
期刊介绍: Physica D (Nonlinear Phenomena) publishes research and review articles reporting on experimental and theoretical works, techniques and ideas that advance the understanding of nonlinear phenomena. Topics encompass wave motion in physical, chemical and biological systems; physical or biological phenomena governed by nonlinear field equations, including hydrodynamics and turbulence; pattern formation and cooperative phenomena; instability, bifurcations, chaos, and space-time disorder; integrable/Hamiltonian systems; asymptotic analysis and, more generally, mathematical methods for nonlinear systems.
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