基于SEIR的社交網(wǎng)絡(luò)信息傳播模型的研究
發(fā)布時間：2018-11-02 09:20
【摘要】：近年來,隨著科技的進(jìn)步以及互聯(lián)網(wǎng)技術(shù)的發(fā)展,世界各國的社交網(wǎng)站都發(fā)展迅速。在國內(nèi),新浪微博、人人網(wǎng)等社交網(wǎng)站也已經(jīng)擁有數(shù)億的用戶量。社交網(wǎng)站以其高度連通性、用戶覆蓋面廣、信息傳播快捷迅猛等優(yōu)勢,已成為當(dāng)前最重要的信息傳播載體之一。社交網(wǎng)絡(luò)(Social Networking Services,SNS)是Web2.0體系下的技術(shù)應(yīng)用架構(gòu),搭建人與人之間信息共享、網(wǎng)絡(luò)溝通的橋梁,極大地滿足了人們非接觸式的社交需求。然而,SNS在信息傳播上的優(yōu)勢也可能被惡意利用從而造成巨大的損失。因此,理解SNS上信息的傳播機(jī)理和過程,掌握信息在社交網(wǎng)絡(luò)上的傳播規(guī)律具有重要的現(xiàn)實意義。 由于社交網(wǎng)絡(luò)中信息的傳播機(jī)理與自然界中傳染病的傳播機(jī)理具有很多相似的部分,因此本文借鑒圖論方法和傳染病模型的方法進(jìn)行以下方面的研究： 1.通過研究分析社交網(wǎng)絡(luò)上信息傳播的特性,結(jié)合傳染病動力學(xué)模型,在SIR模型的基礎(chǔ)上增加潛伏節(jié)點,用來代表接收到信息的離線用戶。提出了適用于社交網(wǎng)絡(luò)的信息傳播的SEIR模型。 2.使用數(shù)學(xué)工具微分方程推導(dǎo)出該SNS上信息傳播模型的動力學(xué)演化方程組。 3.使用Matlab對推導(dǎo)出的動力學(xué)演化方程組進(jìn)行仿真,分析各個參數(shù)對信息傳播速度和規(guī)模的影響,并且與基于SIR的社交網(wǎng)絡(luò)信息傳播模型進(jìn)行對比,分析該模型的正確性以及準(zhǔn)確性。
[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.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.09
本文編號：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.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.09
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