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Disciplinary knowledge production and diffusion in science

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  • Erjia Yan

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  • Erjia Yan, 2016. "Disciplinary knowledge production and diffusion in science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(9), pages 2223-2245, September.
    • Handle: RePEc:bla:jinfst:v:67:y:2016:i:9:p:2223-2245
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    File URL: http://hdl.handle.net/10.1002/asi.23541
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    Cited by:

    1. Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
    2. Pan, Xuelian & Yan, Erjia & Cui, Ming & Hua, Weina, 2018. "Examining the usage, citation, and diffusion patterns of bibliometric mapping software: A comparative study of three tools," Journal of Informetrics, Elsevier, vol. 12(2), pages 481-493.
    3. Saeed-Ul Hassan & Iqra Safder & Anam Akram & Faisal Kamiran, 2018. "A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 973-996, August.
    4. Houqiang Yu & Yian Liang & Yinghua Xie, 2024. "Predicting Scientific Breakthroughs Based on Structural Dynamic of Citation Cascades," Mathematics, MDPI, vol. 12(11), pages 1-18, June.
    5. Kai Nishikawa, 2023. "How and why are citations between disciplines made? A citation context analysis focusing on natural sciences and social sciences and humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2975-2997, May.
    6. Yujie Zhang & Hongzhen Li & Jingyi Mao & Guoxiu He & Yunhan Yang & Zhuoren Jiang & Yufeng Duan, 2023. "COVID-19: a disruptive impact on the knowledge support of references," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4791-4823, August.
    7. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    8. Wu, Chaojiang & Yan, Erjia & Hill, Chelsey, 2017. "Disciplinary knowledge diffusion in business research," Journal of Informetrics, Elsevier, vol. 11(2), pages 655-668.
    9. Yu-Wei Chang, 2018. "Examining interdisciplinarity of library and information science (LIS) based on LIS articles contributed by non-LIS authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1589-1613, September.
    10. Sergey Kolesnikov & Eriko Fukumoto & Barry Bozeman, 2018. "Researchers’ risk-smoothing publication strategies: Is productivity the enemy of impact?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1995-2017, September.
    11. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).
    12. Mao, Jin & Liang, Zhentao & Cao, Yujie & Li, Gang, 2020. "Quantifying cross-disciplinary knowledge flow from the perspective of content: Introducing an approach based on knowledge memes," Journal of Informetrics, Elsevier, vol. 14(4).

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