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

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Title: Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
Authors: Zhu, Yanfeng, Li, Zheng, Li, Tianyi, Jiang, Lei
Source: PLoS ONE; 2/21/2025, Vol. 20 Issue 2, p1-26, 26p
Subject Terms: PATH analysis (Statistics), INTERNET security, DYNAMIC models, RESEARCH methodology, COMPARATIVE studies
Abstract: 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. [ABSTRACT FROM AUTHOR]
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  Data: Topic recognition and refined evolution path analysis of literature in the field of cybersecurity.
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  Data: <searchLink fieldCode="AR" term="%22Zhu%2C+Yanfeng%22">Zhu, Yanfeng</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Zheng%22">Li, Zheng</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Tianyi%22">Li, Tianyi</searchLink><br /><searchLink fieldCode="AR" term="%22Jiang%2C+Lei%22">Jiang, Lei</searchLink>
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  Data: PLoS ONE; 2/21/2025, Vol. 20 Issue 2, p1-26, 26p
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  Data: <searchLink fieldCode="DE" term="%22PATH+analysis+%28Statistics%29%22">PATH analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22INTERNET+security%22">INTERNET security</searchLink><br /><searchLink fieldCode="DE" term="%22DYNAMIC+models%22">DYNAMIC models</searchLink><br /><searchLink fieldCode="DE" term="%22RESEARCH+methodology%22">RESEARCH methodology</searchLink><br /><searchLink fieldCode="DE" term="%22COMPARATIVE+studies%22">COMPARATIVE studies</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of PLoS ONE is the property of Public Library of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1371/journal.pone.0319201
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        Text: English
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        Type: general
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      – SubjectFull: DYNAMIC models
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              Text: 2/21/2025
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