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Statistics in everyone's backyard: An impact study via citation network analysis.

ABSTRACT: Statistical methodologies are indispensable in data-driven scientific discoveries. In this paper, we make the first effort to understand the impact of recent statistical innovations on other scientific fields. By collecting comprehensive bibliometric data from the Web of Science database for selected statistical journals, we investigate the citation trends and compositions of citing fields over time, and we find increasing citation diversity. Furthermore, in a new setting, we apply a local clustering technique involving personalized PageRank with graph conductance for size selection to find the most relevant statistical innovation for a given external topic in other fields. Through a number of case studies, we show that the results from our citation data analysis align well with our knowledge and intuition about these external topics. Overall, we have found that the statistical theory and methods recently invented by the statistics community have made increasing impact on other scientific fields.

SUBMITTER: Wang L

PROVIDER: S-EPMC9403407 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Statistics in everyone's backyard: An impact study via citation network analysis.

Wang Lijia L Tong Xin X Wang Y X Rachel YXR

Patterns (New York, N.Y.) 20220616 8

Statistical methodologies are indispensable in data-driven scientific discoveries. In this paper, we make the first effort to understand the impact of recent statistical innovations on other scientific fields. By collecting comprehensive bibliometric data from the Web of Science database for selected statistical journals, we investigate the citation trends and compositions of citing fields over time, and we find increasing citation diversity. Furthermore, in a new setting, we apply a local clust ...[more]

PMID: 36033599

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Project description:BackgroundCOVID-19 spread quickly around the world shortly after the first outbreaks of the new coronavirus disease at the end of December 2019, affecting all populations, including pregnant women.ObjectiveThe aim of this study was to analyze the relationship between different publications on COVID-19 in pregnancy and their authors through citation networks, as well as to identify the research areas and to determine the publication that has been the most highly cited.MethodsThe search for publications was carried out through the Web of Science database using terms such as "pregnancy," "SARS-CoV-2," "pregnant," and "COVID-19" for the period between January and December 2020. Citation Network Explorer software was used for publication analysis and VOSviewer software was used to construct the figures. This approach enabled an in-depth network analysis to visualize the connections between the related elements and explain their network structure.ResultsA total of 1330 publications and 5531 citation networks were identified in the search, with July being the month with the largest number of publications, and the United States, China, and England as the countries with the greatest number of publications. The most cited publication was "Clinical characteristics and intrauterine vertical transmission potential of COVID-19 infection in nine pregnant women: a retrospective review of medical records" by Chen and colleagues, which was published in March 2020. Six groups identified as being close in the citation network reflect multidisciplinary research, including clinical characteristics and outcomes in pregnancy, vertical transmission, delivery mode, and psychological impacts of the pandemic on pregnant women.ConclusionsThousands of articles on COVID-19 have been published in several journals since the disease first emerged. Identifying relevant publications and obtaining a global view of the main papers published on COVID-19 and pregnancy can lead to a better understanding of the topic. With the accumulation of scientific knowledge, we now know that the clinical features of COVID-19 during pregnancy are generally similar to those of infected nonpregnant women. There is a small increase in frequency of preterm birth and cesarean birth, related to severe maternal illness. Vaccination for all pregnant women is recommended. Several agents are being evaluated for the treatment of COVID-19, but with minimal or no information on safety in pregnancy. These results could form the basis for further research. Future bibliometric and scientometric studies on COVID-19 should provide updated information to analyze other relevant indicators in this field.

Dataset Information

Statistics in everyone's backyard: An impact study via citation network analysis.

Publications

Statistics in everyone's backyard: An impact study via citation network analysis.

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