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Small-world phenomenon of keywords network based on complex network

Author

Listed:
  • Danhao Zhu

    (United Nations University International Institute of Software Technology)

  • Dongbo Wang

    (Nanjing Agricultural University)

  • Saeed-Ul Hassan

    (United Nations University International Institute of Software Technology)

  • Peter Haddawy

    (United Nations University International Institute of Software Technology)

Abstract

Based on the network comprised of 111,444 keywords of library and information science that are extracted from Scopus, and taken into consideration the major properties of average distance and clustering coefficients, the present authors, with the knowledge of complex network and by means of calculation, reveal the small-world effect of the keywords network. On the basis of the keywords network, the betweenness centrality is used to carry out a preliminary study on how to detect the research hotspots of a discipline. This method is also compared with that of detecting research hotspots by word frequency.

Suggested Citation

  • Danhao Zhu & Dongbo Wang & Saeed-Ul Hassan & Peter Haddawy, 2013. "Small-world phenomenon of keywords network based on complex network," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 435-442, November.
    • Handle: RePEc:spr:scient:v:97:y:2013:i:2:d:10.1007_s11192-013-1019-3
    DOI: 10.1007/s11192-013-1019-3
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    References listed on IDEAS

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    Cited by:

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    2. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
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    6. Zhou, Guangye & Li, Chengren & Li, Tingting & Yang, Yi & Wang, Chen & He, Fangjun & Sun, Jingchang, 2016. "Outer synchronization investigation between WS and NW small-world networks with different node numbers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 506-513.
    7. Xiao Zhou & Lu Huang & Yi Zhang & Miaomiao Yu, 2019. "A hybrid approach to detecting technological recombination based on text mining and patent network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 699-737, November.
    8. Mengyang Wang & Lihe Chai, 2018. "Three new bibliometric indicators/approaches derived from keyword analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 721-750, August.
    9. Cheng, Mengyao & Wu, Jialu & Li, Chaohui & Jia, Yuanxin & Xia, Xiaohua, 2023. "Tele-connection of global agricultural land network: Incorporating complex network approach with multi-regional input-output analysis," Land Use Policy, Elsevier, vol. 125(C).
    10. Tabak, Benjamin Miranda & Silva, Thiago Christiano & Fiche, Marcelo Estrela & Braz, Tércio, 2021. "Citation likelihood analysis of the interbank financial networks literature: A machine learning and bibliometric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).

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