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A quantitative analysis of researcher citation personal display considering disciplinary differences and influence factors

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Abstract

Personal websites are a good place not only for the scientists to show a wealth of content, but also for researchers to excavate some useful information related to quantitative evaluation. Based on researchers’ personal websites this study aims to investigate the degree of citation personal display (CPD) in three major disciplines (chemistry, mathematics, and physics), as well as disciplinary differences in CPD. This paper also studies the factors which have influences on CPD by using binary logistic regression. The datasets studied consisted of 5771 researchers in 39 U.S. universities. Results show that CPD varies significantly by discipline, with chemistry researchers having the highest CPD (15.3%), followed by physics researchers (12.7%), and mathematics researchers (7.1%). The binary logistic models indicate that total citations, h-index, and citations per publication have significantly positive effects on CPD in chemistry; for mathematics, total citations and h-index do; and for physics, only total citations does (p < .05). The significantly positive influence of publication counts occurs in chemistry and mathematics, and significantly negative influences of scientific age and academic rank only appear in chemistry (p < .05).

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grant No. 71273250). We would like to thank the editor and anonymous reviewers for their constructive comments and suggestions, which helped us to improve the paper.

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Authors and Affiliations

  1. School of Management, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, China

    Xingchen Li, Qiang Wu & Yuanyuan Liu

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  1. Xingchen Li
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  2. Qiang Wu
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  3. Yuanyuan Liu
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Corresponding author

Correspondence to Qiang Wu.

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Appendix

See Table 11.

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Li, X., Wu, Q. & Liu, Y. A quantitative analysis of researcher citation personal display considering disciplinary differences and influence factors. Scientometrics 113, 1093–1112 (2017). https://doi.org/10.1007/s11192-017-2501-0

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