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Influence Model of User Behavior Characteristics on Information Dissemination

机译:用户行为特征对信息传播的影响模型

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摘要

Quantitative analysis on human behavior, especially mining and modeling temporal and spatial regularities, is a common focus of statistical physics and complexity sciences. The in-depth understanding of human behavior helps in explaining many complex socioeconomic phenomena, and in finding applications in public opinion monitoring, disease control, transportation system design, calling center services, information recommendation. In this paper,we study the impact of human activity patterns on information diffusion. Using SIR propagation model and empirical data, conduct quantitative research on the impact of user behavior on information dissemination. It is found that when the exponent is small, user behavioral characteristics have features of many new dissemination nodes, fast information dissemination, but information continued propagation time is short, with limited influence; when the exponent is big, there are fewer new dissemination nodes, but will expand the scope of information dissemination and extend information dissemination duration; it is also found that for group behaviors, the power-law characteristic a greater impact on the speed of information dissemination than individual behaviors. This study provides a reference to better understand influence of social networking user behavior characteristics on information dissemination and kinetic effect.
机译:对人类行为的定量分析,尤其是对时间和空间规律的挖掘和建模,是统计物理学和复杂性科学的共同重点。对人类行为的深入理解有助于解释许多复杂的社会经济现象,并有助于在舆论监测,疾病控制,运输系统设计,呼叫中心服务,信息推荐中找到应用。在本文中,我们研究了人类活动模式对信息传播的影响。使用SIR传播模型和经验数据,对用户行为对信息传播的影响进行定量研究。研究发现,当指数较小时,用户行为特征具有许多新的传播节点,快速的信息传播,但信息持续传播时间短,影响有限等特点。指数大时,新的传播节点较少,但会扩大信息传播的范围,延长信息传播的时间。还发现,对于群体行为而言,幂律特性对信息传播速度的影响要大于对个体行为的影响。这项研究为更好地理解社交网络用户行为特征对信息传播和动力学效应的影响提供了参考。

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