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Collective dynamics in knowledge networks: Emerging trends analysis

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  • Liu, Xiang
  • Jiang, Tingting
  • Ma, Feicheng

Abstract

This paper addresses emerging trends in the collective dynamics found in knowledge networks, those networks composed of the relationships among knowledge sources, such as citation networks and keyword networks. In studying the formation and detection of new trends in the process of knowledge evolution, we use the collective dynamics approach to construct a network of knowledge clusters based on citation clustering. This approach explores the processes and rules of new trends emerging in knowledge clusters by examining the continuous changes in keyword vectors found in the interaction and coordination between evolving knowledge clusters. In direct citation networks, the collective dynamics approach is found to be superior to the baseline method, especially in predicting small knowledge fields with less data and more uncertainties.

Suggested Citation

  • Liu, Xiang & Jiang, Tingting & Ma, Feicheng, 2013. "Collective dynamics in knowledge networks: Emerging trends analysis," Journal of Informetrics, Elsevier, vol. 7(2), pages 425-438.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:2:p:425-438
    DOI: 10.1016/j.joi.2013.01.003
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    4. Xiaoguang Wang & Qikai Cheng & Wei Lu, 2014. "Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1253-1271, November.
    5. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
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    9. Li, Xin & Xie, Qianqian & Daim, Tugrul & Huang, Lucheng, 2019. "Forecasting technology trends using text mining of the gaps between science and technology: The case of perovskite solar cell technology," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 432-449.
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