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Mustafa G, Rauf A, Tanvir Afzal M. MRET: Modified Recursive Elimination Technique for ranking author assessment parameters. PLoS One 2024; 19:e0303105. [PMID: 38870157 PMCID: PMC11175400 DOI: 10.1371/journal.pone.0303105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 04/18/2024] [Indexed: 06/15/2024] Open
Abstract
In scientific research, assessing the impact and influence of authors is crucial for evaluating their scholarly contributions. Whereas in literature, multitudinous parameters have been developed to quantify the productivity and significance of researchers, including the publication count, citation count, well-known h index and its extensions and variations. However, with a plethora of available assessment metrics, it is vital to identify and prioritize the most effective metrics. To address the complexity of this task, we employ a powerful deep learning technique known as the Multi-Layer Perceptron (MLP) classifier for the classification and the ranking purposes. By leveraging the MLP's capacity to discern patterns within datasets, we assign importance scores to each parameter using the proposed modified recursive elimination technique. Based on the importance scores, we ranked these parameters. Furthermore, in this study, we put forth a comprehensive statistical analysis of the top-ranked author assessment parameters, encompassing a vast array of 64 distinct metrics. This analysis gives us treasured insights in between these parameters, shedding light on the potential correlations and dependencies that may affect assessment outcomes. In the statistical analysis, we combined these parameters by using seven well-known statistical methods, such as arithmetic means, harmonic means, geometric means etc. After combining the parameters, we sorted the list of each pair of parameters and analyzed the top 10, 50, and 100 records. During this analysis, we counted the occurrence of the award winners. For experimental proposes, data collection was done from the field of Mathematics. This dataset consists of 525 individuals who are yet to receive their awards along with 525 individuals who have been recognized as potential award winners by certain well known and prestigious scientific societies belonging to the fields' of mathematics in the last three decades. The results of this study revealed that, in ranking of the author assessment parameters, the normalized h index achieved the highest importance score as compared to the remaining sixty-three parameters. Furthermore, the statistical analysis results revealed that the Trigonometric Mean (TM) outperformed the other six statistical models. Moreover, based on the analysis of the parameters, specifically the M Quotient and FG index, it is evident that combining these parameters with any other parameter using various statistical models consistently produces excellent results in terms of the percentage score for returning awardees.
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Affiliation(s)
- Ghulam Mustafa
- Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan
| | - Abid Rauf
- Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan
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Alshdadi AA, Usman M, Alassafi MO, Afzal MT, AlGhamdi R. Formulation of rules for the scientific community using deep learning. Scientometrics 2023. [DOI: 10.1007/s11192-023-04633-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Wang HY, Chien TW, Kan WC, Wang CY, Chou W. Authors who contributed most to the fields of hemodialysis and peritoneal dialysis since 2011 using the hT-index: Bibliometric analysis. Medicine (Baltimore) 2022; 101:e30375. [PMID: 36197241 PMCID: PMC9509042 DOI: 10.1097/md.0000000000030375] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The h-index does not take into account the full citation list of a researcher to evaluate individual research achievements (IRAs). As a generalization of the h-index, the hT-index takes all citations into account to evaluate IRAs. Compared to other bibliometric indices, it is unclear whether the hT-index is more closely associated with the h-index. We utilized articles published on hemodialysis and peritoneal dialysis (HD/PD) to validate the hT-index as a measure of the most significant contributions to HD/PD. METHODS Using keywords involving HD/PD in titles, subject areas, and abstracts since 2011, we obtained 7702 abstracts and their associated metadata (e.g., citations, authors, research institutes, countries of origin). In total, 4752 first or corresponding authors with hT-indices >0 were evaluated. To present the author's IRA, the following 4 visualizations were used: radar, Sankey, impact beam plot, and choropleth map to investigate whether the hT-index was more closely associated with the h-index than other indices (e.g., g-/x-indices and author impact factors), whether the United States still dominates the majority of publications concerning PD/HD, and whether there was any difference in research features between 2 prolific authors. RESULTS In HD/PD articles, we observed that (a) the hT-index was closer to and associated with the h-index; (b1) the United States (37.15), China (34.63), and Japan (28.09) had the highest hT-index; (b2) Sun Yat Sen University (Chian) earned the highest hT-index (=20.02) among research institutes; (c1) the authors with the highest hT-indices (=15.64 and 14.39, respectively) were David W Johnson (Australia) and Andrew Davenport (UK); and (c2) their research focuses on PD and HD, respectively. CONCLUSION The hT-index was demonstrated to be appropriate for assessing IRAs along with visualizations. The hT-index is recommended in future bibliometric analyses of IRAs as a complement to the h-index.
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Affiliation(s)
- Hsien-Yi Wang
- Department of Sport Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan
- Ncphrology Department, Chi-Mei Medical Center, Tainan, Taiwan
| | - Tsair-Wei Chien
- Department of Medical Research, Chi-Mei Medical Center, Tainan, Taiwan
| | - Wei-Chih Kan
- Department of Sport Management, College of Leisure and Recreation Management, Chia Nan University of Pharmacy and Science, Tainan, Taiwan
- Department of Biological Science and Technology, Chung Hwa University of Medical Technology, Tainan, Taiwan
| | | | - Willy Chou
- Department of Physical Medicine and Rehabilitation, Chiali Chi-Mei Hospital, Tainan, Taiwan
- Department of Physical Medicine and Rehabilitation, Chung San Medical University Hospital, Taichung, Taiwan
- *Correspondence: Willy Chou, Chi-Mei Medical Center, 901 Chung Hwa Road, Yung Kung Dist., Tainan 710, Taiwan (e-mail: )
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Hassan W, Zafar M, Duarte AE, Kamdem JP, Teixeira da Rocha JB. The silver jubilee of Nitric Oxide Journal: From 1997 to 2021. Nitric Oxide 2022; 124:74-87. [DOI: 10.1016/j.niox.2022.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/16/2022] [Accepted: 05/18/2022] [Indexed: 11/30/2022]
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Wahid N, Warraich NF, Tahira M. Group level scientometric analysis of Pakistani authors. COLLNET JOURNAL OF SCIENTOMETRICS AND INFORMATION MANAGEMENT 2021. [DOI: 10.1080/09737766.2021.1960219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Nazia Wahid
- Library, Fatima Jinnah Women University, Rawalpindi, Pakistan
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Salman M, Ahmed MM, Afzal MT. Assessment of author ranking indices based on multi-authorship. Scientometrics 2021. [DOI: 10.1007/s11192-021-03906-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World. PUBLICATIONS 2021. [DOI: 10.3390/publications9010012] [Citation(s) in RCA: 133] [Impact Index Per Article: 44.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Nowadays, the importance of bibliographic databases (DBs) has increased enormously, as they are the main providers of publication metadata and bibliometric indicators universally used both for research assessment practices and for performing daily tasks. Because the reliability of these tasks firstly depends on the data source, all users of the DBs should be able to choose the most suitable one. Web of Science (WoS) and Scopus are the two main bibliographic DBs. The comprehensive evaluation of the DBs’ coverage is practically impossible without extensive bibliometric analyses or literature reviews, but most DBs users do not have bibliometric competence and/or are not willing to invest additional time for such evaluations. Apart from that, the convenience of the DB’s interface, performance, provided impact indicators and additional tools may also influence the users’ choice. The main goal of this work is to provide all of the potential users with an all-inclusive description of the two main bibliographic DBs by gathering the findings that are presented in the most recent literature and information provided by the owners of the DBs at one place. This overview should aid all stakeholders employing publication and citation data in selecting the most suitable DB.
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An entropy-based measure for the evolution of h index research. Scientometrics 2020. [DOI: 10.1007/s11192-020-03712-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Ranking of author assessment parameters using Logistic Regression. Scientometrics 2020. [DOI: 10.1007/s11192-020-03769-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Important citation identification by exploiting the syntactic and contextual information of citations. Scientometrics 2020. [DOI: 10.1007/s11192-020-03677-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Abstract
Researchers contribute to the frontiers of knowledge by establishing facts and reaching new conclusions through systematic investigations, and by subsequently publishing the outcomes of their research findings in the form of research papers. These research publications are indicative of researchers' scientific impact. Different bibliometric indices have been proposed to measure the impact or productivity of a researcher. These indices include publication count, citation count, number of coauthors, h-index, etc. The h-index, since its inception, has been ranked as the foremost impact indicator by many studies. However, as a consequence of the various short comings identified in h-index, some variants of h-index have been proposed. For instance, one dimension which requires significant attention is determining the ability of exceptional performers in a particular research area. In our study, we have compared effectiveness of h-index and some of its recent variants in identifying the exceptional performers of a field. We have also found correlation of h-index with recently proposed indices. A high correlation indicates same effect of these indices as of h-index and low correlation means these indices make non-redundant contribution while ranking potential researchers of a field of study. So far, effectiveness of these indices has not been explored/validated on real data sets of same field. We have considered these variants/modifications of h-index along with h-index and tested on comprehensive data set for the field of Computer Science. The Award winners’ data set is considered as the benchmark for the evaluation of these indices for individual researchers. Results show that there is a low correlation of these indices with h-index, and in identifying exceptional performers of a field these indices perform better than h-index.
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Ameer M, Afzal MT. Evaluation of h-index and its qualitative and quantitative variants in Neuroscience. Scientometrics 2019. [DOI: 10.1007/s11192-019-03209-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Ain QU, Riaz H, Afzal MT. Evaluation of h-index and its citation intensity based variants in the field of mathematics. Scientometrics 2019. [DOI: 10.1007/s11192-019-03009-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Identification of important citations by exploiting research articles’ metadata and cue-terms from content. Scientometrics 2018. [DOI: 10.1007/s11192-018-2961-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Fenner T, Harris M, Levene M, Bar-Ilan J. A novel bibliometric index with a simple geometric interpretation. PLoS One 2018; 13:e0200098. [PMID: 29990357 PMCID: PMC6039009 DOI: 10.1371/journal.pone.0200098] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 06/19/2018] [Indexed: 11/18/2022] Open
Abstract
We propose the χ-index as a bibliometric indicator that generalises the h-index. While the h-index is determined by the maximum square that fits under the citation curve of an author when plotting the number of citations in decreasing order, the χ-index is determined by the maximum area rectangle that fits under the curve. The height of the maximum rectangle is the number of citations ck to the kth most-cited publication, where k is the width of the rectangle. The χ-index is then defined as [Formula: see text], for convenience of comparison with the h-index and other similar indices. We present a comprehensive empirical comparison between the χ-index and other bibliometric indices, focusing on a comparison with the h-index, by analysing two datasets-a large set of Google Scholar profiles and a small set of Nobel prize winners. Our results show that, although the χ and h indices are strongly correlated, they do exhibit significant differences. In particular, we show that, for these data sets, there are a substantial number of profiles for which χ is significantly larger than h. Furthermore, restricting these profiles to the cases when ck > k or ck < k corresponds to, respectively, classifying researchers as either tending to influential, i.e. having many more than h citations, or tending to prolific, i.e. having many more than h publications.
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Affiliation(s)
- Trevor Fenner
- Department of Computer Science and Information Systems, University of London, London WC1E 7HX, United Kingdom
| | - Martyn Harris
- Department of Computer Science and Information Systems, University of London, London WC1E 7HX, United Kingdom
| | - Mark Levene
- Department of Computer Science and Information Systems, University of London, London WC1E 7HX, United Kingdom
| | - Judit Bar-Ilan
- Department of Information Science, Bar-Ilan University, Ramat Gan, Israel
- * E-mail:
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