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Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends
Wastewater-based epidemiology (WBE) has contributed significantly to the monitoring of drug use and transmission of viruses that has been published in numerous research papers. In this paper, we used LitStraw, a self-developed text extraction tool, to extract, analyze, and construct knowledge graphs...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9867605/ https://www.ncbi.nlm.nih.gov/pubmed/36662433 http://dx.doi.org/10.1007/s11356-023-25237-9 |
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author | Gao, Zhihan Gao, Min Chen, Chun-hua Zhou, Yifan Zhan, Zhi-Hui Ren, Yuan |
author_facet | Gao, Zhihan Gao, Min Chen, Chun-hua Zhou, Yifan Zhan, Zhi-Hui Ren, Yuan |
author_sort | Gao, Zhihan |
collection | PubMed |
description | Wastewater-based epidemiology (WBE) has contributed significantly to the monitoring of drug use and transmission of viruses that has been published in numerous research papers. In this paper, we used LitStraw, a self-developed text extraction tool, to extract, analyze, and construct knowledge graphs from nearly 900 related papers in PDF format collected in Web of Science from 2000 to 2021 to analyze the research hotspots and development trends of WBE. The results showed a growing number of WBE publications in multidisciplinary cross-collaboration, with more publications and close collaboration between the USA, Australia, China, and European countries. The keywords of illicit drugs and pharmaceuticals still maintain research hotness, but the specific research hotspots change significantly, among which the research hotspots of new psychoactive substances, biomarkers, and stability show an increasing trend. In addition, judging the spread of COVID-19 by the presence of SARS-CoV-2 RNA in sewage has become the focus since 2020. This work can show the development of WBE more clearly by constructing a knowledge graph and also provide new ideas for the paper mining analysis methods in different fields. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-023-25237-9. |
format | Online Article Text |
id | pubmed-9867605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-98676052023-01-23 Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends Gao, Zhihan Gao, Min Chen, Chun-hua Zhou, Yifan Zhan, Zhi-Hui Ren, Yuan Environ Sci Pollut Res Int Review Article Wastewater-based epidemiology (WBE) has contributed significantly to the monitoring of drug use and transmission of viruses that has been published in numerous research papers. In this paper, we used LitStraw, a self-developed text extraction tool, to extract, analyze, and construct knowledge graphs from nearly 900 related papers in PDF format collected in Web of Science from 2000 to 2021 to analyze the research hotspots and development trends of WBE. The results showed a growing number of WBE publications in multidisciplinary cross-collaboration, with more publications and close collaboration between the USA, Australia, China, and European countries. The keywords of illicit drugs and pharmaceuticals still maintain research hotness, but the specific research hotspots change significantly, among which the research hotspots of new psychoactive substances, biomarkers, and stability show an increasing trend. In addition, judging the spread of COVID-19 by the presence of SARS-CoV-2 RNA in sewage has become the focus since 2020. This work can show the development of WBE more clearly by constructing a knowledge graph and also provide new ideas for the paper mining analysis methods in different fields. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-023-25237-9. Springer Berlin Heidelberg 2023-01-20 2023 /pmc/articles/PMC9867605/ /pubmed/36662433 http://dx.doi.org/10.1007/s11356-023-25237-9 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Review Article Gao, Zhihan Gao, Min Chen, Chun-hua Zhou, Yifan Zhan, Zhi-Hui Ren, Yuan Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends |
title | Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends |
title_full | Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends |
title_fullStr | Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends |
title_full_unstemmed | Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends |
title_short | Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends |
title_sort | knowledge graph of wastewater-based epidemiology development: a data-driven analysis based on research topics and trends |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9867605/ https://www.ncbi.nlm.nih.gov/pubmed/36662433 http://dx.doi.org/10.1007/s11356-023-25237-9 |
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