社交网络中个体价值分析

摘要

The analysis of individual value in the social network is to use the web crawler to grab the data in the social network, to filter the data, to abstract the graph structure, and to find the highest ranking node (individual). This paper is based on PageRank algorithm, using the golden section line method” and the “Pareto Law” and is used in the social network. Based on the definition to the individual value of human as the core, this model can used in the new fields, and it is called “PeopleRank”. In this paper, the complex social network is abstracted into a graph structure, and the nodes in the graph represent the users, and the edges of the graph represent the relationship between the “fans” and “concerns”. Using the “PeopleRank” model, the matrix is constructed, and the matrix is calculated iteratively. Finally, a convergent result is obtained. According to the obtained results, the importance of the individual in the social network can be determined.%社交网络中个体价值分析，就是利用网络爬虫抓取社交网络中数据，对数据过滤分析，抽象成图结构，发现排名最高的节点（个体）。本文基于PageRank算法模型，应用“黄金分割线”方法和“二八定律”对其进行改进，并用在社交网络中，定义以人为核心的个体价值，这样PageRank模型就有了新的应用领域，同时也有了一个新的名字“PeopleRank”。本文将复杂的社交网络抽象成一种图结构，图中节点代表用户，图中边的链入链出代表了用户之间的“粉丝”和“关注”关系。利用“PeopleRank”模型，构建矩阵，对矩阵进行迭代计算，最后得到一个收敛的结果，根据结果的大小确定在社交网络中个体的重要性。