Differences in impact factor across fields and over time

Althouse, Benjamin M.; West, Jevin D.; Bergstrom, Ted; Bergstrom, Carl T.

doi:10.1002/asi.20936

Cited by 239 publications

(192 citation statements)

References 11 publications

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“…Traditionally, bibliometric approaches have been widely used to determine the scientific and academic merit of a particular journal Althouse, West, Bergstrom, & Bergstrom, 2009) and authors' productivity (Bornmann, Mutz, & Daniel, 2009;McCain, 1990), and for creating thematic maps through co-word or co-occurrence analysis (Callon et al, 1986;Courtial & Law, 1989;He, 1999).…”

Section: The Study Of Scholarly Communication and Research Output In mentioning

confidence: 99%

A bibliometric mapping of the structure of STEM education using co‐word analysis

Assefa

Rorissa

2013

J Am Soc Inf Sci Tec

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STEM, a set of fields that includes science, technology, engineering, and mathematics; allied disciplines ranging from environmental, agricultural, and earth sciences to life science and computer science; and education and training in these fields, is clearly at the top of the list of priority funding areas for governments, including the United States government. The U.S. has 11 federal agencies dedicated to supporting programs and providing funding for research and curriculum development. The domain of STEM education has significant implications in preparing the desired workforce with the requisite knowledge, developing appropriate curricula, providing teachers the necessary professional development, focusing research dollars on areas that have maximum impact, and developing national educational policy and standards. A complex undertaking such as STEM education, which attracts interest and valuable resources from a number of stakeholders needs to be well understood. In light of this, we attempt to describe the underlying structure of STEM education, its core areas, and their relationships through co-word analyses of the titles, keywords, and abstracts of the relevant literature using visualization and bibliometric mapping tools. Implications are drawn with respect to the nature of STEM education as well as curriculum and policy development.

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Section: The Study Of Scholarly Communication and Research Output In mentioning

confidence: 99%

A bibliometric mapping of the structure of STEM education using co‐word analysis

Assefa

Rorissa

2013

J Am Soc Inf Sci Tec

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“…Therefore measurements of performance that are derived from citation count cannot be directly compared across research fields. While analyses of bibliometric indicators were performed previously for multiple research fields (Iglesias and Pecharromán, 2007;Radicchi et al, 2008;Althouse et al, 2009) and subfields (Narin et al, 1976;Vinkler, 1988), they were never studied at the species level. A large number of species are used as experimental subjects in many areas of biological research, including plant and animal science, mycology, bacteriology, and others.…”

Section: Introductionmentioning

confidence: 99%

Analysis of bibliometric indicators to determine citation bias

Šimko

2015

Palgrave Commun

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Citations of research papers and citation-related indicators are frequently used factors in determining research priorities, allocating funding, and deciding appointments, promotions and tenures. The main problem with using citations for a variety of evaluations is a substantial difference in the average number of citations received by papers in different research fields and subfields. A large number of species are subjects of biological research, but the distributions of their citations have not been studied in detail. The key objective of the present work was to determine whether the choice of experimental subjects influence bias in citations. A case study was performed on papers from 108 plant species and five research fields. Funnel plot analyses and computer simulations identified species-related citation bias within all research fields. Relationships between bibliometric indicators imply that species with a fast growing number of publications in recent years (for example, new model organisms) generally have a higher average number of citations per paper than is the overall mean for the research field. In contrast, the average number of citations received by the five most prominent papers of the species was strongly correlated with the total number of published papers from laboratories working with the species. The current study indicates that despite the high frequency of cross-species citations, citations of species show a pattern similar to separate subfields. Although these analyses were performed on plant research papers, the findings have relevance for other areas of research where experimental subjects tend to form separate subfields. To reliably compare citations across subfields, a new type of bibliometric indicator is needed. In the meantime committees evaluating quality of research should take into consideration that citations of papers within a research field might be biased due to the experimental subjects used in the studies.

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“…In particular, the evolution of the 2-year Impact Factor over the years and the stability of the values of single journals in the JCR lists has already been analyzed by several authors. We must mention the papers [35,36], in which the dynamics of the values of this index has been studied, showing its global behavior, including, for example, inflation through a long enough time period as a consequence of the growth of the size of the disciplines. Additionally, from the very beginning of the use of the impact factor for evaluation purposes, some redefinitions of this index have been proposed with the idea of assuring its stability (e.g., [37]).…”

Section: Measuring Stability Of Journal Rankingsmentioning

confidence: 99%

Measuring Time-Dynamics and Time-Stability of Journal Rankings in Mathematics and Physics by Means of Fractional p-Variations

2017

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Journal rankings of specific research fields are often used for evaluation purposes, both of authors and institutions. These rankings can be defined by means of several methods, as expert assessment, scholarly-based agreements, or by the ordering induced by a numeric index associated to the prestige of the journals. In order to be efficient and accepted by the research community, it must preserve the ordering over time, at least up to a point. Otherwise, the procedure for defining the ranking must be revised to assure that it reflects the presumably stable characteristic "prestige" that it claims to be quantifying. A mathematical model based on fractional p-variations of the values of the order number of each journal in a time series of journal rankings is explained, and its main properties are shown. As an example, we study the evolution of two given ordered lists of journals through an eleven-year series. These journal ranks are defined by using the 2-year Impact Factor of Thomson-Reuters (nowadays Clarivate Analytics) lists for MATHEMATICS and PHYSICS, APPLIED from 2002 to 2013. As an application of our model, we define an index that precludes the use of journal ranks for evaluation purposes when some minimal requirements on the associated fractional p-variations are not satisfied. The final conclusion is that the list of mathematics does not satisfy the requirements on the p-variations, while the list of applied physics does.

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Differences in impact factor across fields and over time

Cited by 239 publications

References 11 publications

A bibliometric mapping of the structure of STEM education using co‐word analysis

A bibliometric mapping of the structure of STEM education using co‐word analysis

Analysis of bibliometric indicators to determine citation bias

Measuring Time-Dynamics and Time-Stability of Journal Rankings in Mathematics and Physics by Means of Fractional p-Variations

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