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A bibliometric analysis using machine learning to track paradigm shifts and analytical advances in forest ecology and forestry journal publications from 2010 to 2022

Jin Zhao Liyu Li Jian Liu Yimei Yan Qian Wang Chris Newman Youbing Zhou

Forest Ecosystems2024，Vol.11Issue(5)：P.770-779,10.

Forest Ecosystems2024，Vol.11Issue(5)：P.770-779,10.DOI:10.1016/j.fecs.2024.100233

A bibliometric analysis using machine learning to track paradigm shifts and analytical advances in forest ecology and forestry journal publications from 2010 to 2022

Jin Zhao ¹Liyu Li ²Jian Liu ²Yimei Yan ²Qian Wang ²Chris Newman ³Youbing Zhou¹

作者信息

1. College of Biological&Pharmaceutical Sciences,China Three Gorges University,Daxue Road 8,Yichang 443002,China Hubei International Scientific&Technological Cooperation Center of Ecological Conservation&Management in Three Gorges Area,China Three Gorges University,Daxue Road 8,Yichang 443002,China
2. College of Biological&Pharmaceutical Sciences,China Three Gorges University,Daxue Road 8,Yichang 443002,China
3. Wildlife Conservation Research Unit,Department of Biology,University of Oxford,Oxford,United Kingdom
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摘要

关键词

Forest ecology/Forestry/R software/Structural topic modelling/Machine learning/Publication

分类

农业科技

引用本文复制引用

Jin Zhao,Liyu Li,Jian Liu,Yimei Yan,Qian Wang,Chris Newman,Youbing Zhou..A bibliometric analysis using machine learning to track paradigm shifts and analytical advances in forest ecology and forestry journal publications from 2010 to 2022[J].Forest Ecosystems,2024,11(5):P.770-779,10.

基金项目

financially supported by the National Natural Science Foundation of China(31971541). （31971541）

Forest Ecosystems

OACSTPCD

ISSN：2095-6355

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