基于SEIR的社交网络信息传播模型的研究
发布时间：2018-11-02 09:20
【摘要】：近年来,随着科技的进步以及互联网技术的发展,世界各国的社交网站都发展迅速。在国内,新浪微博、人人网等社交网站也已经拥有数亿的用户量。社交网站以其高度连通性、用户覆盖面广、信息传播快捷迅猛等优势,已成为当前最重要的信息传播载体之一。社交网络(Social Networking Services,SNS)是Web2.0体系下的技术应用架构,搭建人与人之间信息共享、网络沟通的桥梁,极大地满足了人们非接触式的社交需求。然而,SNS在信息传播上的优势也可能被恶意利用从而造成巨大的损失。因此,理解SNS上信息的传播机理和过程,掌握信息在社交网络上的传播规律具有重要的现实意义。 由于社交网络中信息的传播机理与自然界中传染病的传播机理具有很多相似的部分,因此本文借鉴图论方法和传染病模型的方法进行以下方面的研究： 1.通过研究分析社交网络上信息传播的特性,结合传染病动力学模型,在SIR模型的基础上增加潜伏节点,用来代表接收到信息的离线用户。提出了适用于社交网络的信息传播的SEIR模型。 2.使用数学工具微分方程推导出该SNS上信息传播模型的动力学演化方程组。 3.使用Matlab对推导出的动力学演化方程组进行仿真,分析各个参数对信息传播速度和规模的影响,并且与基于SIR的社交网络信息传播模型进行对比,分析该模型的正确性以及准确性。
[Abstract]:In recent years, with the progress of science and technology and the development of Internet technology, social networking sites all over the world are developing rapidly. In China, Sina Weibo, Renren.com and other social networking sites have hundreds of millions of users. Social network has become one of the most important carriers of information dissemination because of its high connectivity, wide user coverage, rapid information dissemination and other advantages. Social Network (Social Networking Services,SNS) is a technical application framework under Web2.0 system, which builds the bridge of information sharing and network communication between people, and greatly meets people's non-contact social needs. However, the advantages of SNS in information dissemination may also be maliciously exploited, resulting in huge losses. Therefore, it is of great practical significance to understand the mechanism and process of information dissemination on SNS and to grasp the rules of information dissemination on social networks. Since the mechanism of information transmission in social networks is similar to that of infectious diseases in nature, this paper uses graph theory and infectious disease model for reference to study the following aspects: 1. By studying and analyzing the characteristics of information transmission on social networks, combined with the dynamics model of infectious diseases, the latent nodes are added to the SIR model to represent the offline users who receive the information. This paper presents a SEIR model for information dissemination in social networks. 2. The dynamic evolution equations of the information propagation model on the SNS are derived by using the mathematical tool differential equation. 3. The dynamic evolution equations derived by Matlab are simulated, and the influence of each parameter on the speed and scale of information transmission is analyzed, and compared with the information transmission model of social network based on SIR. The correctness and accuracy of the model are analyzed.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.09
本文编号：2305613
[Abstract]:In recent years, with the progress of science and technology and the development of Internet technology, social networking sites all over the world are developing rapidly. In China, Sina Weibo, Renren.com and other social networking sites have hundreds of millions of users. Social network has become one of the most important carriers of information dissemination because of its high connectivity, wide user coverage, rapid information dissemination and other advantages. Social Network (Social Networking Services,SNS) is a technical application framework under Web2.0 system, which builds the bridge of information sharing and network communication between people, and greatly meets people's non-contact social needs. However, the advantages of SNS in information dissemination may also be maliciously exploited, resulting in huge losses. Therefore, it is of great practical significance to understand the mechanism and process of information dissemination on SNS and to grasp the rules of information dissemination on social networks. Since the mechanism of information transmission in social networks is similar to that of infectious diseases in nature, this paper uses graph theory and infectious disease model for reference to study the following aspects: 1. By studying and analyzing the characteristics of information transmission on social networks, combined with the dynamics model of infectious diseases, the latent nodes are added to the SIR model to represent the offline users who receive the information. This paper presents a SEIR model for information dissemination in social networks. 2. The dynamic evolution equations of the information propagation model on the SNS are derived by using the mathematical tool differential equation. 3. The dynamic evolution equations derived by Matlab are simulated, and the influence of each parameter on the speed and scale of information transmission is analyzed, and compared with the information transmission model of social network based on SIR. The correctness and accuracy of the model are analyzed.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.09
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