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Mapping the intellectual structure of the Internet of Things (IoT) field (2000–2014): a co-word analysis

Author

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  • Bei-Ni Yan

    (Anhui University
    Fu Jen Catholic University)

  • Tian-Shyug Lee

    (Fu Jen Catholic University)

  • Tsung-Pei Lee

    (Fu Jen Catholic University)

Abstract

The study utilized co-word analysis to explore papers in the field of Internet of Things to examine the scientific development in the area. The research data were retrieved from the WOS database from the period between 2000 and 2014, which consists of 758 papers. By using co-word analysis, this study found 7 clusters that represent the intellectual structure of IoT, including ‘IoT and Security’, ‘Middleware’, ‘RFID’, ‘Internet’, ‘Cloud computing’, ‘Wireless sensor networks’ and ‘6LoWPAN’. To understand these intellectual structures, this study used a co-occurrence matrix based on Pearson’s correlation coefficient to create a clustering of the words using the hierarchical clustering technique. To visualize these intellectual structures, this study carried out a multidimensional scaling analysis, to which a PROXCAL algorithm was applied.

Suggested Citation

  • Bei-Ni Yan & Tian-Shyug Lee & Tsung-Pei Lee, 2015. "Mapping the intellectual structure of the Internet of Things (IoT) field (2000–2014): a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(2), pages 1285-1300, November.
    • Handle: RePEc:spr:scient:v:105:y:2015:i:2:d:10.1007_s11192-015-1740-1
    DOI: 10.1007/s11192-015-1740-1
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    Cited by:

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    13. Manuel Castriotta & Maria Chiara Guardo, 2016. "Disentangling the automotive technology structure: a patent co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 819-837, May.
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    15. Xiuwen Chen & Jianping Li & Xiaolei Sun & Dengsheng Wu, 2019. "Early identification of intellectual structure based on co-word analysis from research grants," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 349-369, October.
    16. Sujit Bhattacharya & Ravinder Kumar & Shubham Singh, 2020. "Capturing the salient aspects of IoT research: A Social Network Analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 361-384, October.
    17. Xuefeng Wang & Shuo Zhang & Yuqin liu, 2022. "ITGInsight–discovering and visualizing research fronts in the scientific literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6509-6531, November.
    18. Qikai Cheng & Jiamin Wang & Wei Lu & Yong Huang & Yi Bu, 2020. "Keyword-citation-keyword network: a new perspective of discipline knowledge structure analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 1923-1943, September.
    19. Manuel Castriotta & Michela Loi & Elona Marku & Luca Naitana, 2019. "What’s in a name? Exploring the conceptual structure of emerging organizations," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 407-437, February.
    20. Zhu, Lin & Cunningham, Scott W., 2022. "Unveiling the knowledge structure of technological forecasting and social change (1969–2020) through an NMF-based hierarchical topic model," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    21. Qing Yang & Yanxia Zhu & Xingxing Liu & Lingmei Fu & Qianqian Guo, 2019. "Bayesian-Based NIMBY Crisis Transformation Path Discovery for Municipal Solid Waste Incineration in China," Sustainability, MDPI, vol. 11(8), pages 1-21, April.
    22. Lu, Yang & Papagiannidis, Savvas & Alamanos, Eleftherios, 2018. "Internet of Things: A systematic review of the business literature from the user and organisational perspectives," Technological Forecasting and Social Change, Elsevier, vol. 136(C), pages 285-297.
    23. Takano, Yasutomo & Kajikawa, Yuya, 2019. "Extracting commercialization opportunities of the Internet of Things: Measuring text similarity between papers and patents," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 45-68.

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