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Proving ground for social network analysis in the emerging research area “Internet of Things” (IoT)

Author

Listed:
  • Arif Mehmood

    (Yeungnam University)

  • Gyu Sang Choi

    (Yeungnam University)

  • Otto F. Feigenblatt

    (Royal Academy of Doctors of Spain)

  • Han Woo Park

    (Yeungnam University)

Abstract

This study examines the structural patterns of international co-institutions and co-authors in science citation index papers in the research domain of the Internet of Things (IoT). The study uses measures from the social network analysis method, including degree centrality, betweenness centrality, eigenvector centrality, and effectiveness, to investigate the effects of social networks. In addition, the study proposes a prediction model for assessing the semantic relevancy of research papers in the field of IoT (Regarding social science approach on semantic analysis, refer to Jung and Park in Gov Inf Q, 2015a. doi: 10.1016/j.giq.2015.09.010 , 32(3):353–358, 2015b). For the analysis, 815 research papers were selected from the Web of Science database for the 1993–2015 period. Empirical analysis results identify China as the most central country, followed by the U.S., Spain, the U.K., and Sweden, in terms of the co-authored network. Similarly, the Chinese Academy of Sciences, the Beijing University of Posts and Telecommunications, and Shanghai Jiao Tong University were ranked first, third, and fourth, respectively, among the top five co-institutions. Northeastern University (U.S.) and the University of Surrey (U.K.) ranked second and fifth, respectively. A confusion matrix was used to validate the accuracy of the proposed model. The accuracy of the prediction model was 76.84 %, whereas recall for the model (ability of a search to find all relevant items in the corpus) was 94.47 %.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:1:d:10.1007_s11192-016-1931-4
    DOI: 10.1007/s11192-016-1931-4
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    References listed on IDEAS

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    1. Gohar Feroz Khan & Sungjoon Lee & Ji Young Park & Han Woo Park, 2016. "Theories in communication science: a structural analysis using webometrics and social network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 531-557, August.
    2. Matthew A. Shapiro & Han Woo Park, 2012. "Regional development in South Korea: accounting for research area in centrality and networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 271-287, January.
    3. Ki-Seok Kwon & Han Woo Park & Minho So & Loet Leydesdorff, 2012. "Has globalization strengthened South Korea’s national research system? National and international dynamics of the Triple Helix of scientific co-authorship relationships in South Korea," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 163-176, January.
    4. Park, Han Woo & Leydesdorff, Loet, 2013. "Decomposing social and semantic networks in emerging “big data” research," Journal of Informetrics, Elsevier, vol. 7(3), pages 756-765.
    5. Wagner, Caroline S. & Leydesdorff, Loet, 2005. "Network structure, self-organization, and the growth of international collaboration in science," Research Policy, Elsevier, vol. 34(10), pages 1608-1618, December.
    6. Sujin Choi & Joshua SungWoo Yang & Han Woo Park, 2015. "The triple helix and international collaboration in science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(1), pages 201-212, January.
    7. Park, Han Woo & Leydesdorff, Loet, 2010. "Longitudinal trends in networks of university-industry-government relations in South Korea: The role of programmatic incentives," Research Policy, Elsevier, vol. 39(5), pages 640-649, June.
    8. Han Woo Park & Loet Leydesdorff, 2008. "Korean journals in the Science Citation Index: What do they reveal about the intellectual structure of S&T in Korea?," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 439-462, June.
    9. Han Park, 2012. "How do social scientists use link data from search engines to understand Internet-based political and electoral communication?," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(2), pages 679-693, February.
    10. George A. Barnett & Han Woo Park & Ke Jiang & Chuan Tang & Isidro F. Aguillo, 2014. "A multi-level network analysis of web-citations among the world’s universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 5-26, April.
    11. 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.
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    Cited by:

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    2. Matheus Becker Costa & Leonardo Moraes Aguiar Lima Santos & Jones Luís Schaefer & Ismael Cristofer Baierle & Elpidio Oscar Benitez Nara, 2019. "Industry 4.0 technologies basic network identification," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 977-994, November.
    3. 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.
    4. Tenvir Ali & Zeeshan Jhandir & Ingyu Lee & Byung-Won On & Gyu Sang Choi, 2017. "Evaluating Retrieval Effectiveness by Sustainable Rank List," Sustainability, MDPI, vol. 9(7), pages 1-20, July.
    5. 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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