微博网络信息流的影响因素研究

发布时间：2018-05-09 05:18

本文选题：微博客 + 信息传播　；参考：《清华大学》2012年硕士论文

【摘要】：作为一个庞大的信息交互平台，微博客系统的巨大商业价值正日益受到重视，而怎样提升信息传播能力也成为了重要的研究问题。现有研究主要集中在简单的网络结构分析或者是基于理想理论模型的信息流分析，目前还未能为控制微博系统中的信息流传播提供可靠的研究成果。因此，本研究希望通过真实的用户网络数据和信息流数据分析微博客系统中的用户网络的结构参数对于信息传播过程的影响。研究共分为4个阶段。第一阶段通过文献和理论回顾，总结了5个指标用来衡量网络结构特性，并建立了6个指标衡量信息传播效果，同时对于结构性指标对信息传播指标所可能产生的潜在影响提出假设。第二阶段收集了由26347个节点及998360个用户间连接关系所组成的用户网络，并追踪了150条信息路径。第三阶段应用社会网络分析方法，对收集的用户网络进行分析，计算各结构性指标。第四阶段分析了不同网络的结构性参数对信息流传播的影响。研究的主要成果如下：（1）节点中心度是衡量节点信息散布能力最重要的指标；间距中心度是衡量个体“中继”信息能力的最好指标；而对于紧密中心度，只有在高于网络中紧密中心度百分比间距80%时，才具有评判个体单位距离内传播信息效率的能力。（2）弱连接是非常重要的信息传递桥梁，在信息传播的路径上它会同时控制更多的节点和级数。但强连接依然在较为紧密的用户群内部起着传递信息的作用。（3）在微博网络中，尽管存在结构上的核，但它对信息的流转和控制力较弱。发生这种情况的原因可能是微博网络中用户行为的不确定性与大量小团体结构的存在。（4）对比三种中心度指标，，间距中心度对于信息的投放选择是最重要的。
[Abstract]:As a huge information exchange platform, the great commercial value of micro-blog system is being paid more and more attention, and how to improve the ability of information dissemination has become an important research issue. The current research focuses on simple network structure analysis or information flow analysis based on ideal theoretical model, but it has not been able to provide reliable research results for controlling the transmission of information flow in Weibo system. Therefore, this study hopes to analyze the influence of user network structure parameters on the process of information dissemination through real user network data and information flow data. The study is divided into four stages. In the first stage, through literature and theoretical review, five indexes are summarized to measure the characteristics of network structure, and six indicators are established to measure the effect of information dissemination. At the same time, the potential impact of structural indicators on information dissemination indicators is hypothesized. In the second stage, a user network consisting of 26347 nodes and 998360 user connections is collected, and 150 information paths are traced. In the third stage, the social network analysis method is used to analyze the collected user networks and calculate the structural indexes. In the fourth stage, the influence of structural parameters of different networks on the propagation of information flow is analyzed. The main results of the study are as follows: (1) Node centrality is the most important index to measure the information dissemination ability of nodes; distance centrality is the best indicator to measure individual "relay" information ability; and for tight centrality, A weak connection is a very important information transmission bridge only if the distance is 80 percent higher than the percentage of tight centrality in the network, and the ability to evaluate the efficiency of information transmission within an individual unit distance is obtained. It controls more nodes and stages at the same time in the path of information transmission. However, the strong connection still plays a role of transmitting information within a relatively close user group. In Weibo network, despite the existence of structural core, its ability to control the flow of information is weak. The reason for this may be that the uncertainty of user behavior in Weibo network is compared with the existence of a large number of small group structures.
【学位授予单位】：清华大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：F49;F224

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