计算机与现代化 ›› 2022, Vol. 0 ›› Issue (04): 65-71.

• 网络与通信 • 上一篇    下一篇

新型冠状病毒肺炎综述文献的网络结构分析

  

  1. (新疆财经大学统计与数据科学学院,新疆乌鲁木齐830012) 
  • 出版日期:2022-05-07 发布日期:2022-05-07
  • 作者简介:贾芳弟(1995—),女,甘肃天水人,硕士研究生,研究方向:复杂网络,社团发现,E-mail: fangdi3@foxmail.com; 刘继(1974—),男,四川达州人,教授,博士,研究方向:网络舆情,数据智能分析,E-mail: liuji5000@126.com。
  • 基金资助:
    国家自然科学基金资助项目(72164034); 新疆维吾尔自治区社会科学基金资助项目(19BTJ036); 新疆维吾尔自治区高校科研计划项目(XJEDU2019SI006)

Analysis on Network Structure of COVID-19’s Review Literature

  1. (School of Statistics and Data Science, Xinjiang University of Finance and Economics, Urumqi 830012, China)
  • Online:2022-05-07 Published:2022-05-07

摘要: 对新型冠状病毒肺炎综述文献进行网络结构分析可为新冠疫情的应对提供有效的理论支持。采用可视化软件CiteSpace对Web of Science数据库中新型冠状病毒肺炎综述文献的引文数据进行共被引网络分析,经统计发现文献共被引网络的度分布呈幂律分布,网络连通性较强且存在小世界现象。运用团渗流算法对其进行重叠社团挖掘,检测到7篇同时跨3个社团的核心文献,结合被引频次对网络重叠节点的功能进行验证。借助网络重叠节点的ID符号、介数中心性指标发现相应研究主题间联系紧密。通过不同特征的重要网络节点,能够有效挖掘到相关的研究主题。

关键词: 新型冠状病毒肺炎, 文献共被引网络, 重叠社团发现, CiteSpace

Abstract: The analysis of the network structure of COVID-19’s review literature can provide effective theoretical support for COVID-19’s response to the epidemic situation. The co-citation network analysis of COVID-19’s review literature in Web of Science database is carried out by using visualization software CiteSpace. Through statistics, it is found that the degree distribution of literature co-citation network is power-law distribution, network connectivity is strong and there is a small-world phenomenon. The clique percorlation method is used to mine the overlapping communities, and seven core literatures which span three communities at the same time are detected. Combined with the cited frequency, the function of the network overlapping nodes is verified. With the help of ID symbols and intermediate centrality index of network overlapping nodes, it is found that the corresponding research topics are closely related. Through the important network nodes with different characteristics, we can effectively mine the relevant research topics.

Key words: COVID-19, literature co-citation network, overlapping community detection, CiteSpace