From informal to formal: scientific knowledge role transition prediction-Reference-Cited by-同舟云学术

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From informal to formal: scientific knowledge role transition prediction

Published:2024-07-12 Issue: Volume: Page:
ISSN:0138-9130
Container-title:Scientometrics
language:en
Short-container-title:Scientometrics

Author:

Yang Jinqing,Liu Zhifeng,Huang Yong

Funder

Youth Program of the National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11192-024-05093-1.pdf

Reference32 articles.

1. Agostini, L., Nosella, A., Sarala, R., Spender, J. C., & Wegner, D. (2020). Tracing the evolution of the literature on knowledge management in inter-organizational contexts: A bibliometric analysis. Journal of Knowledge Management, 24(2), 463–490.

2. Behrouzi, S., Sarmoor, Z. S., Hajsadeghi, K., & Kavousi, K. (2020). Predicting scientific research trends based on link prediction in keyword networks. Journal of Informetrics, 14(4), 101079.

3. Carley, S. F., Newman, N. C., Porter, A. L., & Garner, J. G. (2018). An indicator of technical emergence. Scientometrics, 115(1), 35–49.

4. Chen, B., Tsutsui, S., Ding, Y., & Ma, F. (2017). Understanding the topic evolution in a scientific domain: An exploratory study for the field of information retrieval. Journal of Informetrics, 11(4), 1175–1189.

5. Choi, J., Yi, S., & Lee, K. C. (2011). Analysis of keyword networks in MIS research and implications for predicting knowledge evolution. Information & Management, 48(8), 371–381.

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