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The k-step h-index in citation networks at the paper, author, and institution levels

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  • Yang, Alex Jie
  • Wu, Linwei
  • Zhang, Qi
  • Wang, Hao
  • Deng, Sanhong

Abstract

The evaluation of scientific impact plays a crucial role in assessing research contributions. In this study, we introduce the concept of the k-step h-index and investigate its applicability in citation networks at different levels, including papers, authors, and institutions. By incorporating higher generations of citation information, the k-step h-index provides a comprehensive and nuanced measure of scientific influence. It demonstrates exponential growth in k-step citations, capturing valuable information from the Hirsch core and tail. Through power law distribution analysis, we uncover the presence of highly influential entities coexisting with less influential ones, revealing the heterogeneity of impact within citation networks. To validate the effectiveness of the k-step h-index, we utilize a vast dataset from APS, conducting a thorough examination of its consistency and convergent validity. Our findings demonstrate strong correlations between the k-step h-index and conventional metrics, as well as alignment with measures of innovation. This confirms the reliability of the k-step h-index and its ability to capture innovative contributions. Notably, when compared to benchmarks, the k-step h-index outperforms in accurately ranking expert-selected items, including milestone papers, distinguished authors, and prestigious institutions. Higher values of the k-step h-index consistently exhibit superior performance, showcasing their predictive power in identifying prominent scientific entities. These findings hold significant implications for research evaluation, policy-making, and strategic planning, as they pave the way for a more holistic understanding of scholarly contributions.

Suggested Citation

  • Yang, Alex Jie & Wu, Linwei & Zhang, Qi & Wang, Hao & Deng, Sanhong, 2023. "The k-step h-index in citation networks at the paper, author, and institution levels," Journal of Informetrics, Elsevier, vol. 17(4).
    • Handle: RePEc:eee:infome:v:17:y:2023:i:4:s1751157723000810
    DOI: 10.1016/j.joi.2023.101456
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    as
    1. Mingyang Wang & Jiaqi Zhang & Shijia Jiao & Xiangrong Zhang & Na Zhu & Guangsheng Chen, 2020. "Important citation identification by exploiting the syntactic and contextual information of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2109-2129, December.
    2. Wang, Jingjing & Xu, Shuqi & Mariani, Manuel S. & Lü, Linyuan, 2021. "The local structure of citation networks uncovers expert-selected milestone papers," Journal of Informetrics, Elsevier, vol. 15(4).
    3. Shaibu Mohammed & Anthony Morgan & Emmanuel Nyantakyi, 2020. "On the influence of uncited publications on a researcher’s h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1791-1799, March.
    4. Zhao, Star X. & Rousseau, Ronald & Ye, Fred Y., 2011. "h-Degree as a basic measure in weighted networks," Journal of Informetrics, Elsevier, vol. 5(4), pages 668-677.
    5. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    6. Joshua Ettinger & Friederike E. L. Otto & E. Lisa F. Schipper, 2021. "Storytelling can be a powerful tool for science," Nature, Nature, vol. 589(7842), pages 352-352, January.
    7. Gangan Prathap, 2019. "Letter to the editor: Revisiting the h-index and the p-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1829-1833, December.
    8. Xin An & Xin Sun & Shuo Xu, 2022. "Important citations identification with semi-supervised classification model," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6533-6555, November.
    9. Zhai, Li & Yan, Xiangbin & Zhang, Guojing, 2018. "Bi-directional h-index: A new measure of node centrality in weighted and directed networks," Journal of Informetrics, Elsevier, vol. 12(1), pages 299-314.
    10. Michael Park & Erin Leahey & Russell J. Funk, 2023. "Papers and patents are becoming less disruptive over time," Nature, Nature, vol. 613(7942), pages 138-144, January.
    11. Fang Zhang & Shengli Wu, 2021. "Measuring academic entities’ impact by content-based citation analysis in a heterogeneous academic network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7197-7222, August.
    12. Mariani, Manuel Sebastian & Medo, Matúš & Zhang, Yi-Cheng, 2016. "Identification of milestone papers through time-balanced network centrality," Journal of Informetrics, Elsevier, vol. 10(4), pages 1207-1223.
    13. Lutz Bornmann & Loet Leydesdorff, 2018. "Count highly-cited papers instead of papers with h citations: use normalized citation counts and compare “like with like”!," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1119-1123, May.
    14. Yian Yin & Yang Wang & James A. Evans & Dashun Wang, 2019. "Quantifying the dynamics of failure across science, startups and security," Nature, Nature, vol. 575(7781), pages 190-194, November.
    15. Holly N. Wolcott & Matthew J. Fouch & Elizabeth R. Hsu & Leo G. DiJoseph & Catherine A. Bernaciak & James G. Corrigan & Duane E. Williams, 2016. "Modeling time-dependent and -independent indicators to facilitate identification of breakthrough research papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 807-817, May.
    16. Henry H. Bi, 2023. "Four problems of the h-index for assessing the research productivity and impact of individual authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2677-2691, May.
    17. Russell J. Funk & Jason Owen-Smith, 2017. "A Dynamic Network Measure of Technological Change," Management Science, INFORMS, vol. 63(3), pages 791-817, March.
    18. Jeff Alstott & Ed Bullmore & Dietmar Plenz, 2014. "powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    19. L. Egghe, 2010. "On the relation between Schubert’s h-index of a single paper and its total number of received citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 115-117, July.
    20. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    21. Bornmann, Lutz & Tekles, Alexander, 2021. "Convergent validity of several indicators measuring disruptiveness with milestone assignments to physics papers by experts," Journal of Informetrics, Elsevier, vol. 15(3).
    22. Brito, Ricardo & Navarro, Alonso Rodríguez, 2021. "The inconsistency of h-index: A mathematical analysis," Journal of Informetrics, Elsevier, vol. 15(1).
    23. Vladlen Koltun & David Hafner, 2021. "The h-index is no longer an effective correlate of scientific reputation," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-16, June.
    24. Linyuan Lü & Tao Zhou & Qian-Ming Zhang & H. Eugene Stanley, 2016. "The H-index of a network node and its relation to degree and coreness," Nature Communications, Nature, vol. 7(1), pages 1-7, April.
    25. Henry H. Bi, 2023. "Correction to: Four problems of the h-index for assessing the research productivity and impact of individual authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2693-2699, May.
    26. Ludo Waltman & Nees Jan van Eck, 2012. "The inconsistency of the h-index," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(2), pages 406-415, February.
    27. Ludo Waltman & Nees Jan van Eck, 2012. "The inconsistency of the h‐index," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(2), pages 406-415, February.
    28. András Schubert, 2009. "Using the h-index for assessing single publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(3), pages 559-565, March.
    29. Zhai, Li & Yan, Xiangbin & Zhang, Guojing, 2019. "The bi-directional h-index and B-core decomposition in directed networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    30. Shalabh, 2021. "Statistical inference via data science," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1155-1155, July.
    31. Dunaiski, Marcel & Geldenhuys, Jaco & Visser, Willem, 2018. "How to evaluate rankings of academic entities using test data," Journal of Informetrics, Elsevier, vol. 12(3), pages 631-655.
    32. Xu, Shuqi & Mariani, Manuel Sebastian & Lü, Linyuan & Medo, Matúš, 2020. "Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data," Journal of Informetrics, Elsevier, vol. 14(1).
    33. Gerardo Iñiguez & Carlos Pineda & Carlos Gershenson & Albert-László Barabási, 2022. "Dynamics of ranking," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    34. Mariani, Manuel Sebastian & Medo, Matúš & Lafond, François, 2019. "Early identification of important patents: Design and validation of citation network metrics," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 644-654.
    35. Xiaojun Hu & Ronald Rousseau, 2017. "Nobel Prize winners 2016: Igniting or sparking foundational publications?," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 1053-1063, February.
    36. Martin Rosvall & Alcides V. Esquivel & Andrea Lancichinetti & Jevin D. West & Renaud Lambiotte, 2014. "Memory in network flows and its effects on spreading dynamics and community detection," Nature Communications, Nature, vol. 5(1), pages 1-13, December.
    37. Diana Hicks & Paul Wouters & Ludo Waltman & Sarah de Rijcke & Ismael Rafols, 2015. "Bibliometrics: The Leiden Manifesto for research metrics," Nature, Nature, vol. 520(7548), pages 429-431, April.
    38. Fengli Xu & Lingfei Wu & James Evans, 2022. "Flat teams drive scientific innovation," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(23), pages 2200927119-, June.
    39. Zhenbin Yan & Qiang Wu & Xingchen Li, 2016. "Do Hirsch-type indices behave the same in assessing single publications? An empirical study of 29 bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1815-1833, December.
    40. Shouhuai Xu & Moti Yung & Jingguo Wang, 2021. "Seeking Foundations for the Science of Cyber Security," Information Systems Frontiers, Springer, vol. 23(2), pages 263-267, April.
    41. Fontana, Magda & Iori, Martina & Montobbio, Fabio & Sinatra, Roberta, 2020. "New and atypical combinations: An assessment of novelty and interdisciplinarity," Research Policy, Elsevier, vol. 49(7).
    42. Wu, Lingfei & Kittur, Aniket & Youn, Hyejin & Milojević, Staša & Leahey, Erin & Fiore, Stephen M. & Ahn, Yong-Yeol, 2022. "Metrics and mechanisms: Measuring the unmeasurable in the science of science," Journal of Informetrics, Elsevier, vol. 16(2).
    43. Jian Wang, 2013. "Citation time window choice for research impact evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 851-872, March.
    44. Ruan, Xuanmin & Lyu, Dongqing & Gong, Kaile & Cheng, Ying & Li, Jiang, 2021. "Rethinking the disruption index as a measure of scientific and technological advances," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    45. Yian Yin & Yuxiao Dong & Kuansan Wang & Dashun Wang & Benjamin F. Jones, 2022. "Public use and public funding of science," Nature Human Behaviour, Nature, vol. 6(10), pages 1344-1350, October.
    46. B Ian Hutchins & Xin Yuan & James M Anderson & George M Santangelo, 2016. "Relative Citation Ratio (RCR): A New Metric That Uses Citation Rates to Measure Influence at the Article Level," PLOS Biology, Public Library of Science, vol. 14(9), pages 1-25, September.
    47. Leo Egghe, 2008. "Modelling successive h-indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 77(3), pages 377-387, December.
    48. Jean J. Wang & Sarah X. Shao & Fred Y. Ye, 2021. "Identifying 'seed' papers in sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6001-6011, July.
    49. 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.
    50. Henry H. Bi, 2023. "Correction to: Four problems of the h‑index for assessing the research productivity and impact of individual authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2701-2701, May.
    51. András Schubert, 2007. "Successive h-indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(1), pages 201-205, January.
    52. J. E. Hirsch, 2019. "hα: An index to quantify an individual’s scientific leadership," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(2), pages 673-686, February.
    53. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
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