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Evaluation and Trend of Smart Clothing Research: Visualization Analysis Based on Bibliometric Analysis and Quantitative Statistics

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Abstract

Smart clothing encompass research in interdisciplinary fields such as industrial design, material applications, computer science, and medical services, and have witnessed rapid development over the past decade. Therefore, for scholars, keeping pace with emerging research trends and the evolution of knowledge is crucial. However, due to the wide array of disciplines involved in smart clothing and the wealth of information they encompass, scholars find it challenging to comprehensively grasp the knowledge structure, making it a time-consuming and highly complex task to identify the forefront of research hotspots. To provide a deeper insight into the knowledge framework and emerging trends in the field of smart clothing, this study is based on bibliometric analysis methods. It combines these methods with visualization analysis tools such as Citespace, VOSviewer, Scimago Graphica, and the AntConc corpus analysis tool. First, a dataset comprising 30,860 SCI papers, including research and review papers is collected. Secondly, a comprehensive analysis is conducted using co-occurrence analysis, core citation analysis, core collaboration analysis, and cutting-edge research analysis. Finally, a systematic knowledge framework for smart clothing is constructed. This study combines quantitative text analysis with knowledge visualization analysis to construct a more diverse and detailed knowledge map of smart clothing from multiple perspectives. Simultaneously, it tracks and summarizes the development of smart clothing, providing researchers in the field with a systematic research context and analysis of emerging trends.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was supported by Jieyang Polytechnic [grant numbers 2023JYCKY03].

Funding

This work was supported by Jieyang Polytechnic [grant numbers 2023JYCKY03].

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  1. Department of Arts and Physical Education, Jieyang Polytechnic, Jieyang, China

    Zhe-Hui Lin & Pei-Jie Chen

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  1. Zhe-Hui Lin
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Lin, ZH., Chen, PJ. Evaluation and Trend of Smart Clothing Research: Visualization Analysis Based on Bibliometric Analysis and Quantitative Statistics. Fibers Polym 25, 1479–1511 (2024). https://doi.org/10.1007/s12221-024-00521-8

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