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TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics
By reviewing scientific literature, researchers may obtain a comprehensive understanding of field developments, keeping abreast of the current research status and hotspot shifts. The evolution pattern of keywords is supposed to be an efficient indicator in revealing the shifting and sustainability c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9685342/ https://www.ncbi.nlm.nih.gov/pubmed/36438984 http://dx.doi.org/10.3389/fdata.2022.1045513 |
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author | Liu, Bing Shi, Mengfan Kuang, Yi Jiang, Xin |
author_facet | Liu, Bing Shi, Mengfan Kuang, Yi Jiang, Xin |
author_sort | Liu, Bing |
collection | PubMed |
description | By reviewing scientific literature, researchers may obtain a comprehensive understanding of field developments, keeping abreast of the current research status and hotspot shifts. The evolution pattern of keywords is supposed to be an efficient indicator in revealing the shifting and sustainability configuration of scientific concepts, ideas, and research hotspots. Here we take an extensive investigation of the evolution of keywords among all publications in PNAS Social Sciences from 1990 to 2021. Statistical tests show the keyword mention time series always accompanied by the emergence of a log-normal distribution. Additionally, we introduce a novel schema of four patterns (TELS), which are Transient impact type, Explosive impact type, Large impact type, and Small impact type, respectively, to illustrate the evolution of keywords. The TELS schema can be used to capture the whole life circle feature of any proposed keyword, from a pool of candidates. By dividing the entire time into four periods, we also introduce the concept of elite keywords to reveal the temporal feature of social sciences focus. An explicit transition from anthropology research to neuroscience and social problems research can be observed from the evolution diagram. We argue that the proposed method is of general sense and might be applicable to other fields of science. |
format | Online Article Text |
id | pubmed-9685342 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96853422022-11-25 TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics Liu, Bing Shi, Mengfan Kuang, Yi Jiang, Xin Front Big Data Big Data By reviewing scientific literature, researchers may obtain a comprehensive understanding of field developments, keeping abreast of the current research status and hotspot shifts. The evolution pattern of keywords is supposed to be an efficient indicator in revealing the shifting and sustainability configuration of scientific concepts, ideas, and research hotspots. Here we take an extensive investigation of the evolution of keywords among all publications in PNAS Social Sciences from 1990 to 2021. Statistical tests show the keyword mention time series always accompanied by the emergence of a log-normal distribution. Additionally, we introduce a novel schema of four patterns (TELS), which are Transient impact type, Explosive impact type, Large impact type, and Small impact type, respectively, to illustrate the evolution of keywords. The TELS schema can be used to capture the whole life circle feature of any proposed keyword, from a pool of candidates. By dividing the entire time into four periods, we also introduce the concept of elite keywords to reveal the temporal feature of social sciences focus. An explicit transition from anthropology research to neuroscience and social problems research can be observed from the evolution diagram. We argue that the proposed method is of general sense and might be applicable to other fields of science. Frontiers Media S.A. 2022-11-10 /pmc/articles/PMC9685342/ /pubmed/36438984 http://dx.doi.org/10.3389/fdata.2022.1045513 Text en Copyright © 2022 Liu, Shi, Kuang and Jiang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Big Data Liu, Bing Shi, Mengfan Kuang, Yi Jiang, Xin TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics |
title | TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics |
title_full | TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics |
title_fullStr | TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics |
title_full_unstemmed | TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics |
title_short | TELS: Evolution patterns of research keywords from the evidence of PNAS Social Sciences topics |
title_sort | tels: evolution patterns of research keywords from the evidence of pnas social sciences topics |
topic | Big Data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9685342/ https://www.ncbi.nlm.nih.gov/pubmed/36438984 http://dx.doi.org/10.3389/fdata.2022.1045513 |
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