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Clustering citation histories in the Physical Review

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  • Colavizza, Giovanni
  • Franceschet, Massimo

Abstract

We investigate publications through their citation histories – the history events are the citations given to the article by younger publications and the time of the event is the date of publication of the citing article. We propose a methodology, based on spectral clustering, to group citation histories, and the corresponding publications, into communities and apply multinomial logistic regression to provide the revealed communities with semantics in terms of publication features. We study the case of publications from the full Physical Review archive, covering 120 years of physics in all its domains. We discover two clear archetypes of publications – marathoners and sprinters – that deviate from the average middle-of-the-roads behaviour, and discuss some publication features, like age of references and type of publication, that are correlated with the membership of a publication into a certain community.

Suggested Citation

  • Colavizza, Giovanni & Franceschet, Massimo, 2016. "Clustering citation histories in the Physical Review," Journal of Informetrics, Elsevier, vol. 10(4), pages 1037-1051.
    • Handle: RePEc:eee:infome:v:10:y:2016:i:4:p:1037-1051
    DOI: 10.1016/j.joi.2016.07.009
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    Cited by:

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    4. Zhichao Fang & Rodrigo Costas, 2020. "Studying the accumulation velocity of altmetric data tracked by Altmetric.com," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 1077-1101, May.
    5. Jianhua Hou & Xiucai Yang, 2019. "Patent sleeping beauties: evolutionary trajectories and identification methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 187-215, July.
    6. Mayra Z Rodriguez & Cesar H Comin & Dalcimar Casanova & Odemir M Bruno & Diego R Amancio & Luciano da F Costa & Francisco A Rodrigues, 2019. "Clustering algorithms: A comparative approach," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-34, January.
    7. Lutz Bornmann & Adam Y. Ye & Fred Y. Ye, 2017. "Sequence analysis of annually normalized citation counts: an empirical analysis based on the characteristic scores and scales (CSS) method," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1665-1680, December.
    8. Katchanov, Yurij L. & Markova, Yulia V., 2022. "Dynamics of senses of new physics discourse: Co-keywords analysis," Journal of Informetrics, Elsevier, vol. 16(1).

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