基于网络分析的微博用户特性研究

发布时间：2018-02-01 18:26

本文关键词： 复杂网络微博网络无标度适应度中心度　出处：《湖南师范大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着因特网技术与应用的进一步深入,微博、论坛等社交网络得到了迅猛的发展,并逐步形成了一个至关重要的信息传播平台。微博网络是基于现实生活中的社会关系建立的,它是对我们现实生活的一个映射,所以对微博网络的研究有助于我们深入地了解和认识用户在现实中的社会关系、兴趣等等。国内最大的社交网络是新浪微博,用户数量已经有5.4亿。为了更好地了解微博网络的特征及用户在信息传播中的地位,本文选取“新浪微博”作为研究对象,运用复杂网络理论和社会网络的分析方法,对微博网络进行分析研究。本文的研究结果为运用无标度、适应度理论来研究微博网络内信息的传播提供了理论和实践参考。同时,基于中心度的分析让我们能更方便地确定用户在信息传播过程中的重要程度,具有重要的理论价值和现实意义。本论文的主要研究工作如下： 1)阐述微博网络的研究背景、发展现状和研究意义。介绍复杂网络的基本参数,度分布、聚类系数、平均路径长度；介绍复杂网络的三个网络模型,即小世界模型、无标度模型、适应度模型；介绍社会网络分析法的基本概念,重点介绍中心度的概念。 2)通过新浪微博的开放平台,调用提供的API获取用户信息,即实验数据的获取,以朋友关系构成微博网络。通过对微博网络的数据分析,发现微博网络具有较短的平均路径长度和较高的聚类系数,验证微博网络的小世界特性,此外,发现微博网络中节点的度分布服从幂律分布,表明微博网络具有无标度特性；通过分析网络中不同节点的度随时间的变化情况,发现微博网络中存在适应度特性。 3)运用社会网络的分析方法,研究新浪微博网络中各用户在信息传播过程中所发挥的作用及用户在网络中的重要性。基于社会网络分析方法中的中心度分析,通过计算出各节点的点度中心度、紧密中心度、中间中心度,从不同的侧重点分析网络中各用户所处位置的重要程度,从而确定在网络的信息传播过程中不同用户所起的作用。
[Abstract]:With the further development of Internet technology and application, Weibo, forum and other social networks have been rapidly developed. And gradually formed a crucial information dissemination platform. Weibo network is based on the real life of social relations, it is a mapping of our real life. Therefore, the study of Weibo network helps us to understand and understand the social relations and interests of users in reality. The biggest social network in China is Sina Weibo, which has 540 million users. In order to better understand the characteristics of Weibo network and the status of users in the dissemination of information. This article selects "Sina Weibo" as the research object, uses the complex network theory and the social network analysis method, carries on the analysis research to Weibo network. The fitness theory provides a theoretical and practical reference for the study of the dissemination of information in the Weibo network. At the same time, the centeredness analysis makes it easier for us to determine the importance of users in the process of information dissemination. It has important theoretical value and practical significance. The main research work of this thesis is as follows: 1) the research background, development status and significance of Weibo network are described. The basic parameters, degree distribution, clustering coefficient and average path length of complex network are introduced. This paper introduces three network models of complex network, that is, small world model, scale-free model and fitness model. This paper introduces the basic concept of social network analysis, focusing on the concept of centrality. 2) through the open platform of Sina Weibo, calling the API to obtain the user information, that is, the acquisition of experimental data, the network of Weibo is composed of friends, and the data analysis of Weibo network is carried out. It is found that Weibo network has shorter average path length and higher clustering coefficient, which verifies the small-world characteristic of Weibo network. In addition, it is found that the degree distribution of nodes in Weibo network obeys the power-law distribution. It is shown that the Weibo network has scale-free characteristics. By analyzing the variation of the degree of different nodes with time in the network, it is found that the fitness characteristic exists in the Weibo network. 3) using the analysis method of social network. This paper studies the role of users in the process of information dissemination in Sina Weibo network and the importance of users in the network. By calculating the vertex center degree, tight center degree and intermediate center degree of each node, the importance degree of each user's position in the network is analyzed from different emphasis. In order to determine the network in the process of information dissemination of different users play a role.
【学位授予单位】：湖南师范大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.092

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