A keyword-based approach to analyzing scientific research trends: ReRAM present and future

Abstract Research trend analysis is a primary step in defining research structures and predicting research directions from scientific papers. Recently, due to millions of annual scientific publications, researchers demand analytical methods to interpret the research field topologically and temporall...

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Main Authors: Hyeon Kim, Seong Hun Kim, Jaeseon Kim, Eun Ho Kim, Jun Hyeong Gu, Donghwa Lee
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-93423-5
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author Hyeon Kim
Seong Hun Kim
Jaeseon Kim
Eun Ho Kim
Jun Hyeong Gu
Donghwa Lee
author_facet Hyeon Kim
Seong Hun Kim
Jaeseon Kim
Eun Ho Kim
Jun Hyeong Gu
Donghwa Lee
author_sort Hyeon Kim
collection DOAJ
description Abstract Research trend analysis is a primary step in defining research structures and predicting research directions from scientific papers. Recently, due to millions of annual scientific publications, researchers demand analytical methods to interpret the research field topologically and temporally. In this study, we propose a keyword-based research trend analysis method that automatically and systematically analyzes the research field by extracting keywords and constructing a keyword network. We verified our method on the resistive random-access memory (ReRAM) research field, which is in the limelight as an alternative device for non-volatile memory and artificial synapses. Our method performs three sequential processes: article collection, keyword extraction, and research structuring. We identified three keyword communities of ReRAM based on the processing-structure-property-performance (PSPP) relationship and found an upward trend in Neuromorphic applications. As a result, our method successfully structures the ReRAM research field and is expected to provide detailed insights into various research fields.
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spelling doaj-art-3b4cd8d176bd4f0e870df4a3ef3a998b2025-08-20T03:10:07ZengNature PortfolioScientific Reports2045-23222025-04-0115111010.1038/s41598-025-93423-5A keyword-based approach to analyzing scientific research trends: ReRAM present and futureHyeon Kim0Seong Hun Kim1Jaeseon Kim2Eun Ho Kim3Jun Hyeong Gu4Donghwa Lee5Department of Materials Science and Engineering (MSE), Pohang University of Science and Technology (POSTECH)Department of Materials Science and Engineering (MSE), Pohang University of Science and Technology (POSTECH)Department of Materials Science and Engineering (MSE), Pohang University of Science and Technology (POSTECH)Department of Materials Science and Engineering (MSE), Pohang University of Science and Technology (POSTECH)Department of Materials Science and Engineering (MSE), Pohang University of Science and Technology (POSTECH)Department of Materials Science and Engineering (MSE), Pohang University of Science and Technology (POSTECH)Abstract Research trend analysis is a primary step in defining research structures and predicting research directions from scientific papers. Recently, due to millions of annual scientific publications, researchers demand analytical methods to interpret the research field topologically and temporally. In this study, we propose a keyword-based research trend analysis method that automatically and systematically analyzes the research field by extracting keywords and constructing a keyword network. We verified our method on the resistive random-access memory (ReRAM) research field, which is in the limelight as an alternative device for non-volatile memory and artificial synapses. Our method performs three sequential processes: article collection, keyword extraction, and research structuring. We identified three keyword communities of ReRAM based on the processing-structure-property-performance (PSPP) relationship and found an upward trend in Neuromorphic applications. As a result, our method successfully structures the ReRAM research field and is expected to provide detailed insights into various research fields.https://doi.org/10.1038/s41598-025-93423-5Research trend analysisBibliometricsNetwork theoryNatural Language processingReRAMMaterials science
spellingShingle Hyeon Kim
Seong Hun Kim
Jaeseon Kim
Eun Ho Kim
Jun Hyeong Gu
Donghwa Lee
A keyword-based approach to analyzing scientific research trends: ReRAM present and future
Scientific Reports
Research trend analysis
Bibliometrics
Network theory
Natural Language processing
ReRAM
Materials science
title A keyword-based approach to analyzing scientific research trends: ReRAM present and future
title_full A keyword-based approach to analyzing scientific research trends: ReRAM present and future
title_fullStr A keyword-based approach to analyzing scientific research trends: ReRAM present and future
title_full_unstemmed A keyword-based approach to analyzing scientific research trends: ReRAM present and future
title_short A keyword-based approach to analyzing scientific research trends: ReRAM present and future
title_sort keyword based approach to analyzing scientific research trends reram present and future
topic Research trend analysis
Bibliometrics
Network theory
Natural Language processing
ReRAM
Materials science
url https://doi.org/10.1038/s41598-025-93423-5
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