Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical Effects
This study employs text mining techniques to conduct a systematic quantitative analysis of cybersecurity-related scientific publications and technological research. It aims to break through the limitations of traditional unidirectional evolutionary research, reveal the knowledge evolution rules betw...
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| Format: | Article |
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MDPI AG
2025-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/12/6865 |
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| author | Yin Feng Zheng Li Tao Zhang |
| author_facet | Yin Feng Zheng Li Tao Zhang |
| author_sort | Yin Feng |
| collection | DOAJ |
| description | This study employs text mining techniques to conduct a systematic quantitative analysis of cybersecurity-related scientific publications and technological research. It aims to break through the limitations of traditional unidirectional evolutionary research, reveal the knowledge evolution rules between scientific theories and technical practices in this field, and provide valuable references and decision-making support for optimizing the collaborative innovation ecosystem. Firstly, we took academic papers and patent research on cybersecurity from 2005 to 2024 as the research objects and divided them into ten stages according to the time series. Subsequently, we identified scientific and technological topics and formed science–technology topics to assess their similarity. Then, we selected 3040 pairs of collaborative topic pairs and categorized them into three distinct groups: weak, moderate, and strong correlation. Finally, we constructed a science–technology topic association evolution atlas and analyzed the types of evolutionary pathways of topic associations and their mechanisms of action accordingly. The results demonstrate five evolutionary patterns in science–technology topic associations: division, merging, inheritance, co-occurrence, and independent development. Additionally, the science–technology topics demonstrate a high degree of collaboration, exhibiting a collaborative effect of “initial accumulation–fluctuating differentiation–deep collaboration”. Meanwhile, the correlation evolution of strongly related science–technology topics presents a symmetrical effect of “technology–science–technology” and “science–technology/technology–science”. |
| format | Article |
| id | doaj-art-b3f6d2eaaf8243088ec9decbd810850a |
| institution | Kabale University |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-b3f6d2eaaf8243088ec9decbd810850a2025-08-20T03:26:10ZengMDPI AGApplied Sciences2076-34172025-06-011512686510.3390/app15126865Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical EffectsYin Feng0Zheng Li1Tao Zhang2School of Marxism, Harbin University, Harbin 150086, ChinaSchool of Information Management, Heilongjiang University, Harbin 150080, ChinaSchool of Information Management, Heilongjiang University, Harbin 150080, ChinaThis study employs text mining techniques to conduct a systematic quantitative analysis of cybersecurity-related scientific publications and technological research. It aims to break through the limitations of traditional unidirectional evolutionary research, reveal the knowledge evolution rules between scientific theories and technical practices in this field, and provide valuable references and decision-making support for optimizing the collaborative innovation ecosystem. Firstly, we took academic papers and patent research on cybersecurity from 2005 to 2024 as the research objects and divided them into ten stages according to the time series. Subsequently, we identified scientific and technological topics and formed science–technology topics to assess their similarity. Then, we selected 3040 pairs of collaborative topic pairs and categorized them into three distinct groups: weak, moderate, and strong correlation. Finally, we constructed a science–technology topic association evolution atlas and analyzed the types of evolutionary pathways of topic associations and their mechanisms of action accordingly. The results demonstrate five evolutionary patterns in science–technology topic associations: division, merging, inheritance, co-occurrence, and independent development. Additionally, the science–technology topics demonstrate a high degree of collaboration, exhibiting a collaborative effect of “initial accumulation–fluctuating differentiation–deep collaboration”. Meanwhile, the correlation evolution of strongly related science–technology topics presents a symmetrical effect of “technology–science–technology” and “science–technology/technology–science”.https://www.mdpi.com/2076-3417/15/12/6865LDA2Vectopic identificationtopic association evolutioncollaborative effectsymmetrical effect |
| spellingShingle | Yin Feng Zheng Li Tao Zhang Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical Effects Applied Sciences LDA2Vec topic identification topic association evolution collaborative effect symmetrical effect |
| title | Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical Effects |
| title_full | Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical Effects |
| title_fullStr | Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical Effects |
| title_full_unstemmed | Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical Effects |
| title_short | Research on the Evolutionary Pathway of Science–Technology Topic Associations: Discovering Collaborative and Symmetrical Effects |
| title_sort | research on the evolutionary pathway of science technology topic associations discovering collaborative and symmetrical effects |
| topic | LDA2Vec topic identification topic association evolution collaborative effect symmetrical effect |
| url | https://www.mdpi.com/2076-3417/15/12/6865 |
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