ArticleDigital health
Google Trends applications for COVID-19 pandemic: A bibliometric analysis.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Spatiotemporal evolution of online interest in assisted reproductive technology: a two-decade global analysis through google trends.BMC public health · 2025Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.