本文選題：微博信息傳播網(wǎng)絡(luò) + 復(fù)雜網(wǎng)絡(luò)��； 參考：《太原理工大學(xué)》2014年碩士論文

【摘要】：微博是最近幾年才發(fā)展起來的新興事物,它是互聯(lián)網(wǎng)領(lǐng)域的一個里程碑,微博的出現(xiàn)徹底改變了人們的日常行為方式。微博自誕生以來就憑借其操作簡單和功能實(shí)用等優(yōu)點(diǎn)迅速吸引了數(shù)量龐大的用戶群。微博信息傳播屬性的研究可以從用戶關(guān)系網(wǎng)絡(luò)、信息傳播網(wǎng)絡(luò)和傳播機(jī)制三個方面出發(fā)。微博中用戶是微博的主體和核心,用戶之間的“關(guān)注”和“被關(guān)注”關(guān)系形成了一個關(guān)系網(wǎng)絡(luò),顯然,這個網(wǎng)絡(luò)是有方向的。網(wǎng)絡(luò)是信息傳播的載體,每一個消息帖子的傳播都需要借助該網(wǎng)絡(luò)。 本文首先介紹了微博的一些基本知識,包括微博的概念、國內(nèi)外的研究現(xiàn)狀、發(fā)展歷程、主要應(yīng)用和研究關(guān)鍵問題等。微博是一個復(fù)雜的系統(tǒng),包含了意思不同的各種各樣的特殊符號。它的復(fù)雜性還體現(xiàn)在用戶、微博消息和使用動機(jī)的多樣性,本文對用戶和消息進(jìn)行了分類。信息之所以能夠在微博系統(tǒng)迅速傳播,主要依靠其自身的傳播動力,因此微博傳播動力的研究對深層次地揭示微博特征非常的重要。 微博用戶間的關(guān)系組成一個靜態(tài)網(wǎng)絡(luò)圖,可嘗試從對復(fù)雜網(wǎng)絡(luò)研究的角度去研究微博信息傳播網(wǎng)絡(luò)。本文在大量用戶關(guān)系的數(shù)據(jù)基礎(chǔ)上,構(gòu)建了一個龐大的網(wǎng)絡(luò),利用VC++、Gephi和MATLAB等多種工具分析了網(wǎng)絡(luò)的度、聚類系數(shù)、平均路徑長度、K-核心和社區(qū)等特征值,驗(yàn)證了微博信息網(wǎng)絡(luò)具有小世界、無標(biāo)度的特征,并且其入度和K-核的分布圖具有冪律分布的特點(diǎn),這為后面模型的構(gòu)建和改進(jìn)提供了理論依據(jù)。在特征值相關(guān)性分析中,發(fā)現(xiàn)特征向量中心度與聚類系數(shù)間的相關(guān)系數(shù)很大,它們的關(guān)聯(lián)度很高,這都是衡量網(wǎng)絡(luò)中心性的指標(biāo)。度與圖密度間的關(guān)聯(lián)度也相對較高,而度與特征向量中心度、聚類系數(shù)關(guān)聯(lián)度較低,說明如果一個網(wǎng)絡(luò)的度很大,它的圖密度也一般很大,但中心性可能不強(qiáng),“小世界現(xiàn)象”也就不明顯。在信息傳播網(wǎng)絡(luò)上,提出了三種微元結(jié)構(gòu),通過實(shí)驗(yàn)得出信息分散結(jié)構(gòu)的數(shù)量最多,并且隨著實(shí)驗(yàn)信息鏈的增多,其數(shù)量也逐漸增多。 SI模型、SIS模型和SIR模型是疾病傳播研究領(lǐng)域經(jīng)典的模型,曾經(jīng)為一些流行病的控制起到了決定性的作用。這三種模型主要針對的是生活中疾病的傳播,而疾病的傳播與微博上的信息傳播有所不同,比如疾病的傳播受天氣、氣候等環(huán)境因素的影響,而微博信息的傳播受用戶心情、生活狀況的影響。本文構(gòu)建了一種符合微博信息傳播網(wǎng)絡(luò)的IOSIR模型,該模型考慮到系統(tǒng)的輸入和輸出情況,通過四組不同數(shù)值的模擬仿真,發(fā)現(xiàn)該模型能較準(zhǔn)確地揭示微博的信息傳播過程。
[Abstract]:Micro-blog is a new emerging thing that has developed in recent years. It is a milestone in the Internet field. The appearance of micro-blog has completely changed people's daily behavior. Since its birth, micro-blog has quickly attracted a large number of users with its advantages of simple operation and functional and practical advantages. The research on the information dissemination property of micro-blog can be made. From the three aspects of the user relationship network, the information communication network and the communication mechanism, the users of micro-blog are the main body and core of micro-blog. The "concern" and "concerned" relationship between users form a relational network. Obviously, the network has a direction. The network is the carrier of information dissemination, and the communication of every message post needs to be transmitted. Use the network.
This article first introduces some basic knowledge of micro-blog, including the concept of micro-blog, the current research situation at home and abroad, the development process, the main application and the key problems of research. Micro-blog is a complex system which contains a variety of special symbols with different meanings. Its complexity is also embodied in the variety of users, the messages of micro-blog and the diversity of motivation. This paper classifies users and messages. The reason why information is able to spread rapidly in micro-blog system depends on its own transmission power, so the research on micro-blog's transmission power is very important to reveal the features of micro-blog.
The relationship between micro-blog users consists of a static network graph, which can try to study the micro-blog information communication network from the perspective of complex network research. Based on the data of a large number of user relations, this paper constructs a huge network, and analyzes the degree, clustering coefficient, and average path length of the network by using VC++, Gephi and MATLAB. The eigenvalues of K- core and community verify that the micro-blog information network has the characteristics of a small world and no scaling, and its admission and K- kernel distribution maps have the characteristics of power law distribution. This provides a theoretical basis for the construction and improvement of the latter model. In the correlation analysis of eigenvalues, the correlation between the center degree of the eigenvector and the clustering coefficient is found. The coefficient is very high, and the degree of association is very high. This is the index of the centrality of the network. The degree of correlation between the degree and the graph density is also relatively high. The degree and the center degree of the eigenvector and the clustering coefficient are relatively low. It shows that if the degree of a network is very large, the density of the graph is also very large, but the centrality may not be strong, "small world phenomenon". It is not obvious. In the information communication network, three kinds of microelement structures are proposed. The number of information dispersing structures is the most in the experiment, and the number of the information chain is increasing with the increase of the experimental information chain.
SI model, SIS model and SIR model are classic models in the field of disease transmission research, which have played a decisive role in the control of some epidemics. These three models mainly focus on the spread of diseases in life, and the spread of diseases is different from that on micro-blog. For example, the spread of diseases is affected by weather, climate and other environmental factors. The transmission of micro-blog information is affected by the mood of the users and the influence of the living conditions. This paper constructs a IOSIR model which conforms to the micro-blog information communication network. The model takes into account the input and output of the system, and finds that the model can reveal the information dissemination process of micro-blog more accurately through four different numerical simulation simulations.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.092

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 葛紅美;何炎祥;陳強(qiáng);徐超;;一種基于時間片的微博用戶分類方法[J];小型微型計(jì)算機(jī)系統(tǒng);2013年11期

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本文編號：2000899