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The w‐index: A measure to assess scientific impact by focusing on widely cited papers

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  • Qiang Wu

Abstract

Based on the principles of the h‐index, I propose a new measure, the w‐index, as a particularly simple and more useful way to assess the substantial impact of a researcher's work, especially regarding excellent papers. The w‐index can be defined as follows: If w of a researcher's papers have at least 10w citations each and the other papers have fewer than 10(w+1) citations, that researcher's w‐index is w. The results demonstrate that there are noticeable differences between the w‐index and the h‐index, because the w‐index plays close attention to the more widely cited papers. These discrepancies can be measured by comparing the ranks of 20 astrophysicists, a few famous physical scientists, and 16 Price medalists. Furthermore, I put forward the w(q)‐index to improve the discriminatory power of the w‐index and to rank scientists with the same w. The factor q is the least number of citations a researcher with w needed to reach w+1. In terms of both simplicity and accuracy, the w‐index or w(q)‐index can be widely used for evaluation of scientists, journals, conferences, scientific topics, research institutions, and so on.

Suggested Citation

  • Qiang Wu, 2010. "The w‐index: A measure to assess scientific impact by focusing on widely cited papers," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(3), pages 609-614, March.
    • Handle: RePEc:bla:jamist:v:61:y:2010:i:3:p:609-614
    DOI: 10.1002/asi.21276
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    Cited by:

    1. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    2. Wei, Shelia X. & Tong, Tong & Rousseau, Ronald & Wang, Wanru & Ye, Fred Y., 2022. "Relations among the h-, g-, ψ-, and p-index and offset-ability," Journal of Informetrics, Elsevier, vol. 16(4).
    3. Liao, Huchang & Tang, Ming & Li, Zongmin & Lev, Benjamin, 2019. "Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators," Omega, Elsevier, vol. 88(C), pages 223-236.
    4. Madiha Ameer & Muhammad Tanvir Afzal, 2019. "Evaluation of h-index and its qualitative and quantitative variants in Neuroscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 653-673, November.
    5. Qurat-ul Ain & Hira Riaz & Muhammad Tanvir Afzal, 2019. "Evaluation of h-index and its citation intensity based variants in the field of mathematics," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 187-211, April.
    6. Liwei Cai & Jiahao Tian & Jiaying Liu & Xiaomei Bai & Ivan Lee & Xiangjie Kong & Feng Xia, 2019. "Scholarly impact assessment: a survey of citation weighting solutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 453-478, February.
    7. Brandão, Luana Carneiro & Soares de Mello, João Carlos Correia Baptista, 2019. "A multi-criteria approach to the h-index," European Journal of Operational Research, Elsevier, vol. 276(1), pages 357-363.
    8. Zhou Chunlei & Kong Xiangyi & Lin Zhipeng, 2019. "Research on Derek John de Solla Price Medal Prediction Based on Academic Credit Analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 159-175, January.
    9. Xiaomei Bai & Fuli Zhang & Jinzhou Li & Zhong Xu & Zeeshan Patoli & Ivan Lee, 2021. "Quantifying scientific collaboration impact by exploiting collaboration-citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7993-8008, September.
    10. Muhammad Usman & Ghulam Mustafa & Muhammad Tanvir Afzal, 2021. "Ranking of author assessment parameters using Logistic Regression," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 335-353, January.

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