Evaluation of h-index and its qualitative and quantitative variants in Neuroscience
- 185 Downloads
In the scientific community, different parameters such as, publications, citations, h-index and different variants of h-index are being used to rank the authors. Authors ranking assists in various objectives, including scientific domain expert’s selection and subsequently utilizing their services for different purposes. It can also be used in ranking institutions, selecting journal’s editors, tenure appointments and awarding promotions. There is a need to nominate the best performing index that can rank the authors in a best possible way. All of the existing parameters are either examined on fictional case scenarios or on insufficient datasets belonging to different fields, due to which it is hard to figure out the comparative performance of each index. In order to strongly validate the performance of each individual index these indices should be examined on the large size dataset. This research focuses attention on the evaluation of h-index and some of its variants, both quantitative and qualitative for ranking authors. All these indices are evaluated on a large size dataset belonging to the field of Neuroscience. To evaluate the results of these indices award winners of five different Neuroscience societies are considered as a benchmark. This study will be helpful in distinguishing more dominant authors based on the evaluation results of these quantitative and qualitative indices. In order to evaluate the results obtained from these indices, firstly the correlation among the indices is calculated. Most of the indices such as h-index, hg-index, R-index and m-quotient have strong correlation among them. However, the correlation of f-index with all other indices is weak, which indicates that ranking achieved by the f-index is not similar to others. Secondly the occurrence of award winners in ranked list of each index is calculated and contribution of each index in bringing awardees in top position is checked. None of the index brought 100% of awardees in top positions of the ranking. In quantitative indices hg-index brought maximum 52% awardees in top 10% of its ranked list. While in qualitative indices R-index validated itself as a best performing index by ranking 52% awardees in top 10% of its ranked list. Moreover, it is analyzed that most of the award winners belonging to the SfN (Society for Neuroscience) and CNS (Cognitive Neuroscience Society) lies on the top positions of ranked lists obtained from h-index and hg-index which specify that there might be a relationship between SfN, NAS and the h and hg-indices.
KeywordsAuthors ranking Variants of h-index Neuroscience field Quantitative indices Qualitative indices SfN ANS
- Balog, K., Azzopardi, L., & De Rijke, M. (2006, August). Formal models for expert finding in enterprise corpora. In Proceedings of the 29th annual international ACM SIGIR conference on research and development in information retrieval (pp. 43–50). ACM.Google Scholar
- Bornmann, L., & Marx, W. (2011). The h index as a research performance indicator. European Science Editing, 37(3), 77–80.Google Scholar
- 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 Association for Information Science and Technology, 59(5), 830–837.Google Scholar
- Bornmann, L., Mutz, R., & Daniel, H. D. (2009a). Do we need the h index and its variants in addition to standard bibliometric measures? Journal of the Association for Information Science and Technology, 60(6), 1286–1289.Google Scholar
- Cameron, D. H. L., Aleman-Meza, B., Decker, S., & Arpinar, I. B. (2007). SEMEF: A taxonomy-based discovery of experts, expertise and collaboration networks. Doctoral dissertation, University of Georgia.Google Scholar
- Corder, G. W., & Foreman, D. I. (2009). Comparing variables of ordinal or dichotomous scales: Spearman rank-order, point-biserial, and biserial correlations. In Nonparametric statistics for non-statisticians: A step-by-step approach (pp. 122–154).Google Scholar
- Dorta-González, P., & Dorta-González, M. I. (2013). The student evaluation of teaching and the competence of students as evaluators. arXiv preprint arXiv:1301.7628.
- Egghe, L. (2006). An improvement of the h-index: The g-index. ISSI Newsletter, 2, 8–9.Google Scholar
- Lowry, P., Moody, G., Gaskin, J., Galletta, D., Humphreys, S., Barlow, J., et al. (2013). Evaluating journal quality and the association for information systems (AIS) senior scholars’ journal basket via bibliometric measures: Do expert journal assessments add value?. Rochester: Social Science Research Network.Google Scholar
- Rousseau, R. (2006). New developments related to the Hirsch index. http://eprints.rclis.org/7616/1/Hirsch_new_developments.pdf.
- Waltman, L., & Van Eck, N. J. (2012). The inconsistency of the h-index. Journal of the Association for Information Science and Technology, 63(2), 406–415.Google Scholar
- Wu, Q. (2010). The w-index: A measure to assess scientific impact by focusing on widely cited papers. Journal of the Association for Information Science and Technology, 61(3), 609–614.Google Scholar