Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.

Using text analysis techniques to identify the research topics of the literature in the field of cybersecurity allows us to sort out the evolution of their research topics and reveal their evolution trends. The paper takes the literature from the Web of Science in the field of cybersecurity research...

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Main Authors: Yanfeng Zhu, Zheng Li, Tianyi Li, Lei Jiang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0319201
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author Yanfeng Zhu
Zheng Li
Tianyi Li
Lei Jiang
author_facet Yanfeng Zhu
Zheng Li
Tianyi Li
Lei Jiang
author_sort Yanfeng Zhu
collection DOAJ
description Using text analysis techniques to identify the research topics of the literature in the field of cybersecurity allows us to sort out the evolution of their research topics and reveal their evolution trends. The paper takes the literature from the Web of Science in the field of cybersecurity research from 2003 to 2022 as its research subject, dividing it into ten stages. It then integrates LDA and Word2vec methods for topic recognition and topic evolution analysis. The combined LDA2vec model can better reflect the correlation and evolution patterns between adjacent stage topics, thereby accurately identifying topic features and constructing topic evolution paths. Furthermore, to comprehensively evaluate the effectiveness of the LDA model in topic evolution analysis, this paper introduces the Dynamic Topic Model (DTM) for comparative analysis. The results indicate that the LDA model demonstrates higher applicability and clarity in topic extraction and evolution path depiction. In the aspect of topic content evolution, research topics within the field of cybersecurity exhibit characteristics of complexity and diversity, with some topics even displaying notable instances of backtracking. Meanwhile, within the realm of cybersecurity, there exists a dynamic equilibrium between technological developments and security threats.
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spelling doaj-art-758e4cb19e9d463aaa732b92901349542025-08-20T03:09:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031920110.1371/journal.pone.0319201Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.Yanfeng ZhuZheng LiTianyi LiLei JiangUsing text analysis techniques to identify the research topics of the literature in the field of cybersecurity allows us to sort out the evolution of their research topics and reveal their evolution trends. The paper takes the literature from the Web of Science in the field of cybersecurity research from 2003 to 2022 as its research subject, dividing it into ten stages. It then integrates LDA and Word2vec methods for topic recognition and topic evolution analysis. The combined LDA2vec model can better reflect the correlation and evolution patterns between adjacent stage topics, thereby accurately identifying topic features and constructing topic evolution paths. Furthermore, to comprehensively evaluate the effectiveness of the LDA model in topic evolution analysis, this paper introduces the Dynamic Topic Model (DTM) for comparative analysis. The results indicate that the LDA model demonstrates higher applicability and clarity in topic extraction and evolution path depiction. In the aspect of topic content evolution, research topics within the field of cybersecurity exhibit characteristics of complexity and diversity, with some topics even displaying notable instances of backtracking. Meanwhile, within the realm of cybersecurity, there exists a dynamic equilibrium between technological developments and security threats.https://doi.org/10.1371/journal.pone.0319201
spellingShingle Yanfeng Zhu
Zheng Li
Tianyi Li
Lei Jiang
Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
PLoS ONE
title Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
title_full Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
title_fullStr Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
title_full_unstemmed Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
title_short Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
title_sort topic recognition and refined evolution path analysis of literature in the field of cybersecurity
url https://doi.org/10.1371/journal.pone.0319201
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AT tianyili topicrecognitionandrefinedevolutionpathanalysisofliteratureinthefieldofcybersecurity
AT leijiang topicrecognitionandrefinedevolutionpathanalysisofliteratureinthefieldofcybersecurity