Scientometrics: A Study of Scientific Parameters and Metrics

Scientometrics: A Study of Scientific Parameters and Metrics

Sudeepa Roy Dey (PES Institute of Technology – Bangalore South, India), Archana Mathur (PES Institute of Technology – Bangalore South, India), Gambhire Swati Sampatrao (PES Institute of Technology – Bangalore South, India), Sandesh Sanjay Gade (University of Virginia, USA) and Sai Prasanna (PES Institute of Technology – Bangalore South, India)
Copyright: © 2017 |Pages: 27
DOI: 10.4018/978-1-5225-2498-4.ch017
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The term “Scientometrics” emerges from two significant words –Science and Metrics. It is concerned with metrics used for quantitative analysis of researcher's contribution to various scientific domains. An effective medium to communicate scientific knowledge is via scholarly publications. It provides a platform to propagate research output within and across domains. Thus, there arise need to discover parameters which can measure a researcher's contribution to his field. The most significant metric to measure the impact of a scientific work is citations. The Citation Indexes are utilized as scientometric tool to measure the research output of authors, articles and journals. This book chapter explores the existence of many such scientific parameters at both journal and author level. Further, authors make an earnest attempt to use them to measure the internationality of peer-reviewed journals. They claim that already existing parameters alone are not sufficient for evaluation of internationality and explore new parameters for computing unbiased index both at journal and author level.
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Research activity cannot be performed in isolation. It involves utilization of scientific ideas and techniques established by scholars in a given domain. Researcher experiment with ideas and publish work mostly in peer reviewed scientific journals. Though there are various motivations to cite previous work, authors cite to acknowledge and give credits to the contribution that were already done to the subject matter. This provides insight to build and maintain citation-based indexes and to endorse all Scientists and researchers who made major contributions in the advancement of research and development. In any respect, most scientific parameters have originated from Eugene Garfield’s concept of using bibliographic citations, Impact Factor being the most popular choice. While Impact Factor merely reflects number of citations per publication, H-index, another well known metric, incorporates both number of publications and number of citations in its influence computation. Although many prominent metrics are built using citation indexes, the research community often misuses these indexes and metrics by manipulating the citation count through practices like extensive self-citation, copious citation and at journal level, coercive citation. Researchers often suggest eliminating self-citations from total citation when computing influence. Arguably, self-citation cannot be labeled as unfair or unacceptable if an author choose to cite his related previous work. Copious citations is a practice in which multiple authors profusely cite each other with an intention to raise their h-index and similar influence-governing parameters. There have been similar cases of misuse, where Editor-in-Chief’s of two high impact factor journals are seen publishing extensively not only in their own journals but also into each others’. The journals continue to demonstrate such practice till date hampering the dignity and integrity of the structure of scholarly publications.

Another notable trend, followed opportunistically is when editors of low ranked journals persuade authors to cite their journal with an inclination to push their impact factors. Even though most authors view coercive citation as inappropriate, few low-ranked authors do not mind adding unrelated references and return the favor to publishing journals. If one journal coerces, to improve its rank, others gravitate and this becomes a trend that contaminates the whole publication process. One possible solution could be penalizing the usage of self-citations which would reduce, if does not dethrone, the coercive motivation.

Although journal’s prestige is reflected in its Impact factor, the overall framework of measuring “prestige” and for that matter its “internationality”, demands clear understanding and usage of deep rooted parameters. Scientific indicators like I.F., raw citations, h-index, h5-index, g-index, i-10 index can work as instruments to measure prestige; when it comes to measuring “internationality”, choosing a set of smart indicators and alternatively, defining new, unbiased ones become inevitable. There exist several vague definitions of the term “Internationality” which are based on including attributes like ISSN number, Editorial board members, reviewers, authors, Editors, Publishers and other associated entities of publishing community. Authors refute such definitions and claim that “internationality” should be defined as a quantifiable metric, which is devoid of any kind of misuse or manipulation, is unbiased towards origin of journal, author or article and calibrate journals on the basis of quality of research output it publishes.

The roadmap of the chapter is shown in Figure 1. The chapter is built on two pillars. The first cornerstone lay emphasis upon influence-measuring scientific parameters and examines in depth their merits and demerits. It defines ‘internationality’ of peer-reviewed journal and explores the capacity and degree to which these deep-rooted parameters contribute in computing ‘internationality’. A comparison of new parameter with the existing ones is explained and appropriateness in using these novel parameters is illustrated by citing examples and case study. The chapter moves forward to describe Cobb Douglas Model and mathematically proves its suitability for computing “internationality” of journals. Second pillar of the book chapter highlights the existing metric to measure scholastic influence and talk about new approaches toward author level metrics. It explores “influence” and “internationality” measuring metrics and moves ahead to explore the suitability of SIR and CISER model in their computation. In parallel, contribution of Citation Networks and Genealogy Tree in devising new indicators for author level metrics is also examined.

Figure 1.

Road map “journal metrics”


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