Discoverers in scientific citation data
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Shi, Gui-Yuan
Department of Physics, University of Fribourg, Switzerland
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Kong, Yi-Xiu
Department of Physics, University of Fribourg, Switzerland
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Yuan, Guang-Hui
Fintech Research Institute, Shanghai University of Finance and Economics, Shanghai, China
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Wu, Rui-Jie
Department of Physics, University of Fribourg, Switzerland
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Zeng, An
School of Systems Science, Beijing Normal University, Beijing, China
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Medo, Matúš
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China - Department of Physics, University of Fribourg, Switzerland - Department of Radiation Oncology, Inselspital, University Hospital of Bern and University of Bern, Switzerland
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Published in:
- Journal of Informetrics. - 2019, vol. 13, no. 2, p. 717–725
English
Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to the citation network setting, and show that there are authors who frequently cite recent papers that become highly-cited in the future; these authors are referred to as discoverers. We develop a method for early identification of highly-cited papers based on the early citations from discoverers. The results show that the identified discoverers have a consistent citing pattern over time, and the early citations from them can be used as a valuable indicator to predict the future citation counts of a paper. The discoverers themselves are potential future outstanding researchers as they receive more citations than average.
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Faculty
- Faculté des sciences et de médecine
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Department
- Département de Physique
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Language
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Classification
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Physics
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License
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License undefined
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Identifiers
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Persistent URL
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https://folia.unifr.ch/unifr/documents/308033
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