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Quantifying knowledge from the perspective of information structurization
Scientific literature, as the major medium that carries knowledge between scientists, exhibits explosive growth in the last century. Despite the frequent use of many tangible measures, to quantify the influence of literature from different perspectives, it remains unclear how knowledge is embodied a...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9812334/ https://www.ncbi.nlm.nih.gov/pubmed/36598886 http://dx.doi.org/10.1371/journal.pone.0279314 |
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author | Wang, Xinbing Kang, Huquan Fu, Luoyi Yao, Ling Ding, Jiaxin Wang, Jianghao Gan, Xiaoying Zhou, Chenghu Hopcroft, John E. |
author_facet | Wang, Xinbing Kang, Huquan Fu, Luoyi Yao, Ling Ding, Jiaxin Wang, Jianghao Gan, Xiaoying Zhou, Chenghu Hopcroft, John E. |
author_sort | Wang, Xinbing |
collection | PubMed |
description | Scientific literature, as the major medium that carries knowledge between scientists, exhibits explosive growth in the last century. Despite the frequent use of many tangible measures, to quantify the influence of literature from different perspectives, it remains unclear how knowledge is embodied and measured among tremendous scientific productivity, as knowledge underlying scientific literature is abstract and difficult to concretize. In this regard, there has laid a vacancy in the theoretical embodiment of knowledge for their evaluation and excavation. Here, for the first time, we quantify the knowledge from the perspective of information structurization and define a new measure of knowledge quantification index (KQI) that leverages the extent of disorder difference caused by hierarchical structure in the citation network to represent knowledge production in the literature. Built upon 214 million articles, published from 1800 to 2021, KQI is demonstrated for mining influential classics and laureates that are omitted by traditional metrics, thanks to in-depth utilization of structure. Due to the additivity of entropy and the interconnectivity of the network, KQI assembles numerous scientific impact metrics into one and gains interpretability and resistance to manipulation. In addition, KQI explores a new perspective regarding knowledge measurement through entropy and structure, utilizing structure rather than semantics to avoid ambiguity and attain applicability. |
format | Online Article Text |
id | pubmed-9812334 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-98123342023-01-05 Quantifying knowledge from the perspective of information structurization Wang, Xinbing Kang, Huquan Fu, Luoyi Yao, Ling Ding, Jiaxin Wang, Jianghao Gan, Xiaoying Zhou, Chenghu Hopcroft, John E. PLoS One Research Article Scientific literature, as the major medium that carries knowledge between scientists, exhibits explosive growth in the last century. Despite the frequent use of many tangible measures, to quantify the influence of literature from different perspectives, it remains unclear how knowledge is embodied and measured among tremendous scientific productivity, as knowledge underlying scientific literature is abstract and difficult to concretize. In this regard, there has laid a vacancy in the theoretical embodiment of knowledge for their evaluation and excavation. Here, for the first time, we quantify the knowledge from the perspective of information structurization and define a new measure of knowledge quantification index (KQI) that leverages the extent of disorder difference caused by hierarchical structure in the citation network to represent knowledge production in the literature. Built upon 214 million articles, published from 1800 to 2021, KQI is demonstrated for mining influential classics and laureates that are omitted by traditional metrics, thanks to in-depth utilization of structure. Due to the additivity of entropy and the interconnectivity of the network, KQI assembles numerous scientific impact metrics into one and gains interpretability and resistance to manipulation. In addition, KQI explores a new perspective regarding knowledge measurement through entropy and structure, utilizing structure rather than semantics to avoid ambiguity and attain applicability. Public Library of Science 2023-01-04 /pmc/articles/PMC9812334/ /pubmed/36598886 http://dx.doi.org/10.1371/journal.pone.0279314 Text en © 2023 Wang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wang, Xinbing Kang, Huquan Fu, Luoyi Yao, Ling Ding, Jiaxin Wang, Jianghao Gan, Xiaoying Zhou, Chenghu Hopcroft, John E. Quantifying knowledge from the perspective of information structurization |
title | Quantifying knowledge from the perspective of information structurization |
title_full | Quantifying knowledge from the perspective of information structurization |
title_fullStr | Quantifying knowledge from the perspective of information structurization |
title_full_unstemmed | Quantifying knowledge from the perspective of information structurization |
title_short | Quantifying knowledge from the perspective of information structurization |
title_sort | quantifying knowledge from the perspective of information structurization |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9812334/ https://www.ncbi.nlm.nih.gov/pubmed/36598886 http://dx.doi.org/10.1371/journal.pone.0279314 |
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