图书情报工作 ›› 2018, Vol. 62 ›› Issue (5): 76-86.DOI: 10.13266/j.issn.0252-3116.2018.05.009

• 情报研究 • 上一篇    下一篇

基于信息熵的新媒体环境下网络节点影响力研究——以微信公众号为例

邢云菲1, 王晰巍1,2, 韩雪雯1, 张长亮1   

  1. 1. 吉林大学管理学院信息管理系 长春 130022;
    2. 吉林大学大数据管理研究中心 长春 130022
  • 收稿日期:2017-08-02 修回日期:2017-09-07 出版日期:2018-03-05 发布日期:2018-03-05
  • 作者简介:邢云菲(ORCID:0000-0002-5512-4364),博士研究生,E-mail:787397613@qq.com;王晰巍(ORCID:0000-0002-5850-0126),教授,博士生导师;韩雪雯(ORCID:0000-0001-8477-1969),本科生;张长亮(ORCID:0000-0001-7676-7302),博士研究生。
  • 基金资助:
    本文系国家自然科学基金面上项目"信息生态视角下新媒体信息消费行为机理及服务模式创新研究"(项目编号:71673108)和吉林大学高峰学科(群)建设项目研究成果之一。

Research on the Influence of Network Nodes in New Media Environment Based on Information Entropy: A Case Study of WeChat

Xing Yunfei1, Wang Xiwei1,2, Zhang liu1, Li Shimeng1   

  1. 1. School of Management, Jilin University, Changchun 130022;
    2. Big Data Management Research Center, Jilin University, Changchun 130022
  • Received:2017-08-02 Revised:2017-09-07 Online:2018-03-05 Published:2018-03-05

摘要: [目的/意义]对新媒体环境下网络节点影响力进行研究,能够深入剖析信息传播规律,从而有助于采取针对性措施对信息传播进行合理控制。[方法/过程]基于信息熵理论构建新媒体环境下网络节点影响力模型,以微信公众号为例进行节点影响力测算,对节点直接影响力、间接影响力和综合影响力进行深入分析,最后运用Matlab软件对所构建模型进行仿真分析。[结果/结论]新媒体环境下网络节点综合影响力随着连接节点数量和节点间互动频率增加而增大,直接影响力和间接影响力也以不同幅度增长,但当间接影响力信息熵值超过100时,直接影响力成为影响节点综合影响力的主要因素。

关键词: 信息熵, 新媒体, 节点影响力, 微信

Abstract: [Purpose/significance] The research on the influence of network nodes in new media environment can deeply analyze the law of information dissemination, and thus help to take appropriate measures to control the information dissemination reasonably. [Method/process] This paper constructs the model of users' node influence in the new media environment based on information entropy theory, taking WeChat as an example to analyze the influence of network nodes. By using java programming method, the paper aims to calculate the numerical value of network nodes, including direct influence, indirect influence and total influence. And finally it use Matlab software to simulate the model. [Result/conclusion] Network nodes' total influence increases with the growth in the number of connections and the frequency of interactions between nodes. Direct influence and indirect influence are growing at a different rate, but the direct influence becomes the main factor affecting the comprehensive effect of nodes when the value of indirect influence is over 100.

Key words: information entropy, new media, node influence, Wechat

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