A new approach to compare the scientific impact of scholars

Expand
  • 1 Department of Computational Intelligence, School of computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu –India
    2 Department of Information Technology, Rajkiya Engineering College, Ambedkar Nagar, U.P. India
    3 Department of Computer Science and Engineering, National Institute of Technology Patna. Bihar, India
    4 Department of Database Systems, School of computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu –India
 Corresponding author: Anand Bihari (Email: anand.bihari@vit.ac.in; csanandk@gmail.com).

Received date: 2024-09-19

  Revised date: 2024-12-21

  Accepted date: 2024-12-23

  Online published: 2025-01-20

Abstract

Purpose: Generally, the scientific comparison has been done with the help of the overall impact of scholars. Although it is very easy to compare scholars, but how can we assess the scientific impact of scholars who have different research careers? It is very obvious, the scholars may gain a high impact if they have more research experience or have spent more time (in terms of research career in a year). Then we cannot compare two scholars who have different research careers. Many bibliometrics indicators address the time-span of scholars. In this series, the h-index sequence and EM/EM’-index sequence have been introduced for assessment and comparison of the scientific impact of scholars. The h-index sequence, EM-index sequence, and EM’-index sequence consider the yearly impact of scholars, and comparison is done by the index value along with their component value. The time-series indicators fail to give a comparative analysis between senior and junior scholars if there is a huge difference in both scholars’ research careers.

Design/methodology/approach: We have proposed the cumulative index calculation method to appraise the scientific impact of scholars till that age and tested it with 89 scholars data.

Findings: The proposed mechanism is implemented and tested on 89 scholars’ publication data, providing a clear difference between the scientific impact of two scholars. This also helps in predicting future prominent scholars based on their research impact.

Research limitations: This study adopts a simplistic approach by assigning equal credit to all authors, regardless of their individual contributions. Further, the potential impact of career breaks on research productivity is not taken into account. These assumptions may limit the generalizability of our findings

Practical implications: The proposed method can be used by respected institutions to compare their scholars impact. Funding agencies can also use it for similar purposes.

Originality/value: This research adds to the existing literature by introducing a novel methodology for comparing the scientific impact of scholars. The outcomes of this research have notable implications for the development of more precise and unbiased research assessment frameworks, enabling a more equitable evaluation of scholarly contributions.

Cite this article

Anand Bihari, Sudhakar Tripathi, Akshay Deepak, P. Mohan Kumar . A new approach to compare the scientific impact of scholars[J]. Journal of Data and Information Science, 0 : 1 . DOI: 10.2478/jdis-2025-0013

References

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, 3(4), 273-289.
Bihari, A., & Tripathi, S. (2017). EM-index: a new measure to evaluate the scientific impact of scientists. Scientometrics, 112(1), 659-677.
Bihari, A., & Tripathi, S. (2018). Year based EM-index: a new approach to evaluate the scientific impact of scholars. Scientometrics, 114(3), 1175-1205.
Bihari, A., Tripathi, S., & Deepak, A. (2021). A review on h-index and its alternative indices. Journal of Information Science, 01655515211014478.
Bihari, A., Tripathi, S., Deepak, A., & Kumar, P. (2020). EM-and EM’-index sequence: construction and application in scientific assessment of scholars. MeasurementInterdisciplinary Research and Perspectives, 18(3), 142-157.
Bornmann, L., Mutz, R., & Daniel, H. D. (2008). Are there better indices for evaluation purposes than the h index? A comparison of nine different variants of the h index using data from biomedicine. Journal of the American Society for Information Science and technology, 59(5), 830-837.
Bornmann, L., Mutz, R., Hug, S. E., & Daniel, H. D. (2011). A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5(3), 346-359.
dos Santos Rubem, A. P., & de Moura, A. L. (2015). Comparative analysis of some individual bibliometric indices when applied to groups of researchers. Scientometrics, 102(1), 1019-1035.
Egghe, L. (2006a). An improvement of the h-index: The g-index. ISSI newsletter, 2(1), 8-9.
Egghe, L. (2006b). Theory and practise of the g-index. Scientometrics, 69(1), 131-152.
Egghe, L. (2009). Mathematical study of h-index sequences. Information Processing & Management, 45(2), 288-297.
Egghe, L. (2013). On the correction of the h-index for career length. Scientometrics, 96(2), 563-571.
Fred, Y. Y., & Rousseau, R. (2008). The power law model and total career h-index sequences. Journal of Informetrics, 2(4), 288-297.
Harzing, A. W., Alakangas, S., & Adams, D. (2014). hIa: An individual annual h-index to accommodate disciplinary and career length differences. Scientometrics, 99(3), 811-821.
Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National academy of Sciences, 102(46), 16569-16572.
Huang, M. H., & Chi, P. S. (2010). A comparative analysis of the application of h-index, g-index, and a-index in institutional-level research evaluation. Journal of Library and Information Studies, 8(2), 1-10.
King, J. (1987). A review of bibliometric and other science indicators and their role in research evaluation. Journal of information science, 13(5), 261-276.
Liang, L. (2006). h-index sequence and h-index matrix: Constructions and applications. Scientometrics, 69(1), 153-159.
Liu, Y., & Rousseau, R. (2008). Definitions of time series in citation analysis with special attention to the h-index. Journal of Informetrics, 2(3), 202-210.
Liu, Y., & Yang, Y. (2014). Empirical study of L-Sequence: The basic h-index sequence for cumulative publications with consideration of the yearly citation performance. Journal of Informetrics, 8(3), 478-485.
Mahbuba, D., & Rousseau, R. (2013). Year-based h-type indicators. Scientometrics, 96(3), 785-797.
Mahbuba, D., & Rousseau, R. (2016). New definitions and applications of year-based h-indices. COLLNET Journal of Scientometrics and Information Management, 10(2), 321-332.
Norris, M., & Oppenheim, C. (2010). The h‐index: A broad review of a new bibliometric indicator. Journal of Documentation. 66(5), 756–773.
Schreiber, M., Malesios, C. C., & Psarakis, S. (2012). Exploratory factor analysis for the Hirsch index, 17 h-type variants, and some traditional bibliometric indicators. Journal of Informetrics, 6(3), 347-358.
Derek R. Smith (2015) “Platinum H”: Refining the H-Index to More Realistically Assess Career Trajectory and Scientific Publications. Archives of Environmental & Occupational Health, 70(2), 67-69. DOI: 10.1080/19338244.2015.1016833
Tol, R. (2009). The h-index and its alternatives: An application to the 100 most prolific economists. Scientometrics, 80(2), 317-324.

Wu, J., Lozano, S., & Helbing, D. (2011). Empirical study of the growth dynamics in real career h-index sequences. Journal of Informetrics, 5(4), 489-497.
Outlines

/

京ICP备05002861号-43

Copyright © 2023 All rights reserved Journal of Data and Information Science

E-mail: jdis@mail.las.ac.cn Add:No.33, Beisihuan Xilu, Haidian District, Beijing 100190, China

Support by Beijing Magtech Co.ltd E-mail: support@magtech.com.cn