%0 Journal Article
%T 关于国内新型冠状病毒相关文献的分析研究——基于中国知网抗击新冠疫情知识服务平台<br>Analysis on Domestic Literature Related to Novel Coronavirus
%A 刘海
%A 姚兴兴
%J Hans Journal of Data Mining
%P 36-45
%@ 2163-1468
%D 2023
%I Hans Publishing
%R 10.12677/HJDM.2023.131004
%X 目的：应用文献计量学对国内关于新型冠状病毒的相关文献进行分析和研究，挖掘国内新冠疫情下不同时期的研究热点和发展态势，完善有关的数据材料，为该主题的有关研究提供参考。方法：选取中国知网抗击新冠肺炎疫情知识服务平台的文献，利用VOSviewer、BiComb等文本分析工具，配合Python语言编程，对获得的8038篇中文文献进行分析并可视化结果。结果：高频关键词为作用机理、中医药等，影响力最大的研究领域为医药卫生，发文量最多的机构为华中科技大学，研究热点集中在呼吸系统疾病，刊文量最多的刊物是《中华流行病学杂志》，有科研基金支持的文章有6089项。结论：疫情对各行业的影响逐步扩大，国民对疫情的关注点随时间不断变化，不同领域的研究在国家及社会的支持下陆续开展，高水平论文的发表也屡见不鲜。<br />
Objective: To apply bibliometrics to analyze and study the related literature on novel coronavirus in China, explore the research hotspots and development trends in different periods of the COVID-19 in China, improve the relevant data materials, and provide reference for the related research on this topic. Methods: We select the literature from the knowledge service platform of CNKI to fight against COVID-19, use text analysis tools such as VOSviewer and BiComb, and cooperate with Python language programming to analyze the 8038 Chinese literature obtained and visualize the results. Results: The high-frequency keywords were mechanism of action, traditional Chinese medicine, etc. The research field with the greatest influence was medicine and health, the institution with the largest number of papers was Huazhong University of Science and Technology, the research focus was on respiratory diseases, the journal with the largest number of papers was the Chinese Journal of Epidemiology, and there were 6089 articles supported by scientific research funds. Conclusion: The impact of the epidemic on various industries is gradually expanding, and people’s concerns about the epidemic have changed over time. Research in different fields has been carried out successively with the support of the state and society, and the publication of high-level papers is not uncommon.
%K 新冠疫情，文献计量，数据分析，共现分析<br>COVID-19
%K Bibliometrics
%K Data Analysis
%K Co-Occurrence Analysis
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=60107