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Predicting authors’ citation counts and h-indices with a neural network

Author

Listed:
  • Tobias Mistele

    (Frankfurt Institute for Advanced Studies)

  • Tom Price

    (Frankfurt Institute for Advanced Studies)

  • Sabine Hossenfelder

    (Frankfurt Institute for Advanced Studies)

Abstract

We here describe and present results of a simple neural network that predicts individual researchers’ future citation counts based on a variety of data from the researchers’ past. For publications available on the open access-server arXiv.org we find a higher predictability than previous studies.

Suggested Citation

  • Tobias Mistele & Tom Price & Sabine Hossenfelder, 2019. "Predicting authors’ citation counts and h-indices with a neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 87-104, July.
    • Handle: RePEc:spr:scient:v:120:y:2019:i:1:d:10.1007_s11192-019-03110-2
    DOI: 10.1007/s11192-019-03110-2
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    References listed on IDEAS

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    1. Daniel E. Acuna & Stefano Allesina & Konrad P. Kording, 2012. "Predicting scientific success," Nature, Nature, vol. 489(7415), pages 201-202, September.
    2. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
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    Citations

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    Cited by:

    1. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.
    2. Arash Hajikhani & Arho Suominen, 2022. "Mapping the sustainable development goals (SDGs) in science, technology and innovation: application of machine learning in SDG-oriented artefact detection," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6661-6693, November.
    3. Yuhao Zhou & Ruijie Wang & An Zeng, 2022. "Predicting the impact and publication date of individual scientists’ future papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1867-1882, April.
    4. Wumei Du & Zheng Xie & Yiqin Lv, 2021. "Predicting publication productivity for authors: Shallow or deep architecture?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5855-5879, July.

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