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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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    15. Carlos Olmeda-Gómez & Maria-Antonia Ovalle-Perandones & Antonio Perianes-Rodríguez, 2017. "Co-word analysis and thematic landscapes in Spanish information science literature, 1985–2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 195-217, October.
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    17. Arif Mehmood & Gyu Sang Choi & Otto F. Feigenblatt & Han Woo Park, 2016. "Proving ground for social network analysis in the emerging research area “Internet of Things” (IoT)," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 185-201, October.
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    20. 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.
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    22. 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.
    23. 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).

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