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谷歌趋势在新冠疫情中的应用：一项文献计量分析。

Google Trends applications for COVID-19 pandemic: A bibliometric analysis.

作者信息

Li Hao, Zhang Ning, Ma Xingxing, Wang Yuqing, Yang Feixiang, Wang Wanrong, Huang Yuxi, Xie Yinyin, Du Yinan

机构信息

School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, China.

Department of Urology, First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.

出版信息

Digit Health. 2025 Jan 2;11:20552076241310055. doi: 10.1177/20552076241310055. eCollection 2025 Jan-Dec.

DOI:10.1177/20552076241310055
PMID:39758260
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11696959/
Abstract

INTRODUCTION

COVID-19 is one of the most severe global health events in recent years. Google Trends provides a comprehensive analysis of the search frequency for specific terms on Google, reflecting the public's areas of interest. As of now, there has been no bibliometric study on COVID-19 and Google Trends. Therefore, the aim of this study is to perform a comprehensive bibliometric analysis of existing Google Trends research related to COVID-19.

METHODS

We retrieved 467 records from the Web of Science™ Core Collection, covering the period from January 1, 2020, to December 31, 2023. We then conducted scientific metric analyses using CiteSpace, VOSviewer, and the Bibliometrix package in R-software to explore the temporal and spatial distribution, author distribution, thematic categories, references, and keywords related to these records.

RESULTS

A total of 467 valid records, comprising 418 articles and 49 reviews, were collected for analysis. Over the 4 years, the highest number of publications occurred in 2021. The United States had the most published papers, followed by China. Notably, the United States and China had the closest collaborative relationship. Harvard University ranked as the institution with the highest number of published papers. However, there appeared to be a lack of collaboration between institutions. The research hotspots related to COVID-19 in Google Trends encompassed "outbreak," "epidemic," "air pollution," "internet," "time series," and "public interest."

CONCLUSION

This study provides a valuable overview of the directions in which Google Trends is being utilized for studying infectious diseases, particularly COVID-19.

摘要

引言

新型冠状病毒肺炎（COVID-19）是近年来最严重的全球公共卫生事件之一。谷歌趋势（Google Trends）对谷歌上特定术语的搜索频率进行全面分析，反映公众的关注领域。截至目前，尚未有关于COVID-19与谷歌趋势的文献计量学研究。因此，本研究的目的是对现有的与COVID-19相关的谷歌趋势研究进行全面的文献计量分析。

方法

我们从科学网核心合集（Web of Science™ Core Collection）中检索到467条记录，涵盖2020年1月1日至2023年12月31日期间。然后，我们使用CiteSpace、VOSviewer和R软件中的Bibliometrix包进行科学计量分析，以探索这些记录的时间和空间分布、作者分布、主题类别、参考文献和关键词。

结果

共收集到467条有效记录，包括418篇文章和49篇综述用于分析。在这4年中，2021年的出版物数量最多。美国发表的论文数量最多，其次是中国。值得注意的是，美国和中国的合作关系最为密切。哈佛大学是发表论文数量最多的机构。然而，各机构之间似乎缺乏合作。谷歌趋势中与COVID-19相关的研究热点包括“疫情爆发”“流行病”“空气污染”“互联网”“时间序列”和“公众利益”。

结论

本研究为谷歌趋势在研究传染病，特别是COVID-19方面的应用方向提供了有价值的概述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/e558ab087c58/10.1177_20552076241310055-fig12.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/e558ab087c58/10.1177_20552076241310055-fig12.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/b41905e0a5bd/10.1177_20552076241310055-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/d2b0a6fc256c/10.1177_20552076241310055-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/bacf45dcedaa/10.1177_20552076241310055-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/68579aa35469/10.1177_20552076241310055-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/0632dddd08d7/10.1177_20552076241310055-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/3c4d4306ce17/10.1177_20552076241310055-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/d74e71f75464/10.1177_20552076241310055-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/536a65e70ccf/10.1177_20552076241310055-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/8a6851ddc18c/10.1177_20552076241310055-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/94b4a28b4a4d/10.1177_20552076241310055-fig10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/a6da448618ae/10.1177_20552076241310055-fig11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f4a/11696959/e558ab087c58/10.1177_20552076241310055-fig12.jpg

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