Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends.
Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends.
复制标题
废水流行病学发展知识图谱：基于研究主题和趋势的数据驱动分析
DOI：
10.1007/s11356-023-25237-9
复制
发表时间：
2023-03
影响因子：
5.8
通讯作者：
Ren, Yuan
中科院分区：
文献类型：
--
作者：
Gao, Zhihan;Gao, Min;Chen, Chun-Hua;Zhou, Yifan;Zhan, Zhi-Hui;Ren, Yuan
关键词：
基于废水的流行病学（WBE）对药物使用监测和病毒传播监测做出了重大贡献，这在众多研究论文中均有发表。在本文中，我们使用自行开发的文本提取工具LitStraw，对2000年至2021年从Web of Science收集的近900篇PDF格式的相关论文进行提取、分析并构建知识图谱，以分析WBE的研究热点和发展趋势。结果显示，在多学科交叉合作中，WBE的相关出版物数量不断增加，美国、澳大利亚、中国和欧洲国家之间的出版物更多且合作紧密。非法药物和药品相关的关键词仍然保持研究热度，但具体的研究热点发生了显著变化，其中新型精神活性物质、生物标志物和稳定性的研究热点呈上升趋势。此外，自2020年以来，通过污水中是否存在新冠病毒RNA来判断新冠疫情的传播已成为关注焦点。这项工作通过构建知识图谱能够更清晰地展示WBE的发展，同时也为不同领域的论文挖掘分析方法提供了新思路。
网络版包含补充材料，可在10.1007/s11356 - 023 - 25237 - 9获取。
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.
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DOI：
10.1016/j.cej.2021.129039
发表时间：
2021-07-01
期刊：
Chemical engineering journal (Lausanne, Switzerland : 1996)
影响因子：
--
作者：
Li X;Zhang S;Shi J;Luby SP;Jiang G
通讯作者：
Jiang G
影响因子：
11.8
作者：
Been F;Emke E;Matias J;Baz-Lomba JA;Boogaerts T;Castiglioni S;Campos-Mañas M;Celma A;Covaci A;de Voogt P;Hernández F;Kasprzyk-Hordern B;Laak TT;Reid M;Salgueiro-González N;Steenbeek R;van Nuijs ALN;Zuccato E;Bijlsma L
通讯作者：
Bijlsma L
影响因子：
7.4
作者：
Castiglioni, Sara;Zuccato, Ettore;Bagnati, Renzo
通讯作者：
Bagnati, Renzo
影响因子：
9.8
作者：
Bijlsma, L.;Celma, A.;Zuccato, E.
通讯作者：
Zuccato, E.
影响因子：
9.8
作者：
Gracia-Lor, Emma;Rousis, Nikolaos I.;Castiglioni, Sara
通讯作者：
Castiglioni, Sara