Identification of conversion factor for completing-h index for the field of mathematics

Ayaz, Samreen; Afzal, Muhammad

doi:10.1007/s11192-016-2122-z

Cited by 29 publications

(9 citation statements)

References 21 publications

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“…The power of centrality metrics has been acknowledged by evaluating their capability to identify the awardees of prestigious scientific societies. The awards given by the leading scientific societies are considered for evaluation due to the absence of a benchmark (Ayaz and Afzal 2016). In this study, data of 24 prestigious awards and 671 awardees in mathematics field were collected.…”

Section: Methodsmentioning

confidence: 99%

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A comprehensive author ranking evaluation of network and bibliographic indices

Maqsood

Islam

Afzal

et al. 2020

MJLIS

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With the immense growth of scientific literature over the Web, the authors of research papers are being ranked for various purposes such as for being shortlisted for different scientific awards, for prestigious position, for tenured appointments, for keynote speaker invitation or for allocation of research grants. The traditional paradigm to attain these aspects is based on bibliometric indices, such as publication count, citation count and h-index. The quintessential indicator among all these indices are based on a number of citations received by the publication of an author. Generally, when a research paper is published, it receives citations after some time and may take more than a couple of years to attain a reasonable number of received citations which could make a difference in researcher ranking based on bibliometric parameters. Therefore, dependability over these bibliometric indices for authors ranking is not beneficial for researchers at the start of their academic career. Such authors are less likely to have a fair chance to compete with their senior counterparts. This study aims at overcoming the above-mentioned deficiency with the assistance of network centrality measures using the co-author network. The experiments are conducted to rank authors in order to identify the awardees of various scientific societies. The obtained ranking is further evaluated by comparing the results of bibliographic indices and network-based indices. The results revealed that network indices have equal potential to identify influential authors as compared with bibliometric indices such as h-index, particularly in the case of networks having a high value of cluster coefficient. Based on the obtained results, it is observed, awardees that are exclusively identified by network centrality measures are more than 5 years younger as compared to their counterparts who are exclusively identified by bibliometric indices

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Section: Methodsmentioning

confidence: 99%

“…The steps are delineated in the following sub-sections. There are 57,533 authors and among those 29,263 who have the same last name, have been disambiguated in Ayaz and Afzal (2016) . Whereas 9,403 authors do not have a coauthor relationship, therefore the data related to those authors are omitted from the data set.…”

Section: Methodsmentioning

confidence: 99%

A comprehensive author ranking evaluation of network and bibliographic indices

Maqsood

Islam

Afzal

et al. 2020

MJLIS

Self Cite

View full text Add to dashboard Cite

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“…So, there is need to evaluate usefulness of completing-h on real data set of scientists of different fields. Ayaz & Afzal have evaluated completing-h in the discipline of Mathematics [19]. Prestigious awards given in the field of Mathematics are considered as benchmark.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Thus according to our proposal/assumption, the index which succeeds in bringing award winners in top ranks is the most successful index. Following the Mathematics awardees benchmark dataset [19], we decided to use the awardees dataset for the field of Computer Science as benchmark. For this purpose, we considered prestigious awards given in this field ranging from year 1966 to 2014.…”

Section: Plos Onementioning

confidence: 99%

Comparison of researchers’ impact indices

Ayaz

Masood

2020

PLoS ONE

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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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“…There are multiple sources available to acquire data related to the authors of neuroscience domain such as Web of 1 3 Science (WOS), Google scholar, Scopus etc. However, there is a problem of open access and limited coverage on all other resources except Google scholar (Ayaz and Afzal 2016). Therefore, we collected the neuroscience dataset from Google scholar.…”

Section: Search Enginementioning

confidence: 99%

Evaluation of h-index and its qualitative and quantitative variants in Neuroscience

Ameer

Afzal

2019

Scientometrics

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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.

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Identification of conversion factor for completing-h index for the field of mathematics

Cited by 29 publications

References 21 publications

A comprehensive author ranking evaluation of network and bibliographic indices

A comprehensive author ranking evaluation of network and bibliographic indices

Comparison of researchers’ impact indices

Evaluation of h-index and its qualitative and quantitative variants in Neuroscience

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