Investigating the journal impact along the columns and rows of the publication-citation matrix

AbstractPurposeRamanujacharyulu developed the Power-weakness Ratio (PWR) for scoring tournaments. The PWR algorithm has been advocated (and used) for measuring the impact of journals. We show how such a newly proposed indicator can empirically be tested.Design/methodology/approachPWR values can be found by recursively multiplying the citation matrix by itself until convergence is reached in both the cited and citing dimensions; the quotient of these two values is defined as PWR. We study the effectiveness of PWR using journal ecosystems drawn from the Library and Information Science (LIS) set of the Web of Science (83 journals) as an example. Pajek is used to compute PWRs for the full set, and Excel for the computation in the case of the two smaller sub-graphs: (1) JASIST+ the seven journals that cite JASIST more than 100 times in 2012; and (2) MIS Quart+ the nine journals citing this journal to the same extent.FindingsA test using the set of 83 journals converged, but did not provide interpretable results. Further decomposition of this set into homogeneous sub-graphs shows that—like most other journal indicators—PWR can perhaps be used within homogeneous sets, but not across citation communities. We conclude that PWR does not work as a journal impact indicator; journal impact, for example, is not a tournament.Research limitationsJournals that are not represented on the “citing” dimension of the matrix-for example, because they no longer appear, but are still registered as “cited” (e.g. ARIST)-distort the PWR ranking because of zeros or very low values in the denominator.Practical implicationsThe association of “cited” with “power” and “citing” with “weakness” can be considered as a metaphor. In our opinion, referencing is an actor category and can be studied in terms of behavior, whereas “citedness” is a property of a document with an expected dynamics very different from that of “citing.” From this perspective, the PWR model is not valid as a journal indicator.Originality/valueArguments for using PWR are: (1) its symmetrical handling of the rows and columns in the asymmetrical citation matrix, (2) its recursive algorithm, and (3) its mathematical elegance. In this study, PWR is discussed and critically assessed.

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The integrated interventional radiology match: a bibliometric analysis of matched first-year residents

American Journal of Interventional Radiology ◽

10.25259/ajir_23_2019 ◽

2019 ◽

Vol 3 ◽

pp. 13 ◽

Cited By ~ 1

Author(s):

Vishnu Chandra ◽

Neil Jain ◽

Pratik Shukla ◽

Ethan Wajswol ◽

Sohail Contractor ◽

...

Keyword(s):

Interventional Radiology ◽

Bibliometric Analysis ◽

Statistical Significance ◽

Univariate Analysis ◽

Impact Factors ◽

Index Number ◽

Research Information ◽

H Index ◽

Scopus Database ◽

Journal Impact

Objectives: The integrated interventional radiology (IR) residency has only been established relatively recently as compared to other specialties. Although some preliminary information is available based on survey data five, no comprehensive bibliometric analysis documenting the importance of the quantity and quality of research in applying to an integrated-IR program currently exists. As the first bibliometric analysis of matched IR residents, the data obtained from this study fills a gap in the literature. Materials and Methods: A list of matched residents from the 2018 integrated-IR match were identified by contacting program directors. The Scopus database was used to search for resident research information, including total publications, first-author publications, radiology-related publications, and h-indices. Each matriculating program was categorized into one of five tiers based on the average faculty Hirsch index (h-index). Results: Sixty-three programs and 117 matched residents were identified and reviewed on the Scopus database. For the 2018 cycle, 274 total publications were produced by matched applicants, with a mean of 2.34 ± 0.41 publication per matched applicant. The average h-index for matched applicants was 0.96 ± 0.13. On univariate analysis, the number of radiology-related publications, highest journal impact factor, and h-index were all associated with an increased likelihood of matching into a higher tier program (P < 0.05). Other research variables displayed no statistical significance. All applicants with PhDs matched into tier one programs. Conclusions: Research serves as an important element in successfully matching into an integrated-IR residency. h-index, number of radiology-related manuscripts, and highest journal impact factors are all positively associated with matching into a higher tier program.

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The Socio-economic Context of Journal Impact Factors

Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l'ACSI ◽

10.29173/cais778 ◽

2013 ◽

Author(s):

Brendan Luyt

Keyword(s):

Perceived Value ◽

Modern Society ◽

Impact Factors ◽

Economic Context ◽

Perte D’Autonomie ◽

Journal Impact

This paper argues that the rise of the JIF is a result of the perceived value of quantification measures in modern society and the restructuring of capitalism. Two key implications of this acceptance are explored: an increase in global academic dependency and a lessening of autonomy in the scientific field.Cet article défend la thèse que la montée du FIRS est le résultat de la valeur perçue des mesures de quantification de la société moderne et de la restructuration du capitalisme. Seront explorées deux conséquences importantes de cette acceptation : une augmentation de la dépendance globale du milieu universitaire et une perte d'autonomie du milieu de la science.

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Dynamics of Journal Impact Factors and Limits to Their Inflation

Journal of Scholarly Publishing ◽

10.3138/jsp.50.1.06 ◽

2018 ◽

Vol 50 (1) ◽

pp. 26-36 ◽

Cited By ~ 5

Author(s):

Igor Fischer ◽

Hans-Jakob Steiger

Keyword(s):

Impact Factors ◽

Journal Impact

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Journal Prestige and Journal Impact in Law

SSRN Electronic Journal ◽

10.2139/ssrn.3415599 ◽

2019 ◽

Author(s):

Ignacio Cofone ◽

Pierre-Jean G. Malé

Keyword(s):

Journal Impact

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Altmetrics of COVID-19 research: An analysis of study dissemination by Twitter compared to citation rates (Preprint)

10.2196/preprints.19164 ◽

2020 ◽

Author(s):

Nicholas Fabiano ◽

Zachary Hallgrimson ◽

Sakib Kazi ◽

Jean-Paul Salameh ◽

Stanley Wong ◽

...

Keyword(s):

Social Media ◽

Case Report ◽

Open Access ◽

South America ◽

Negative Binomial ◽

Citation Rate ◽

Sign Test ◽

Study Characteristics ◽

Journal Impact ◽

Epidemic Forecasting

BACKGROUND The COVID-19 pandemic has resulted in over 1,000,000 cases across 181 countries worldwide. The global impact of COVID-19 has resulted in a surge of related research. Researchers have turned to social media platforms, namely Twitter, to disseminate their studies. The online database Altmetric is a tool which tracks the social media metrics of articles and is complementary to traditional, citation-based metrics. Citation-based metrics may fail to portray dissemination accurately, due to the lengthy publication process. Altmetrics are not subject to this time-lag, suggesting that they may be an effective marker of research dissemination during the COVID-19 pandemic. OBJECTIVE To assess the dissemination of COVID-19 research articles as measured by Twitter dissemination, compared to traditional citation-based metrics, and determine study characteristics associated with tweet rates. METHODS COVID-19 studies obtained from LitCovid published between January 1st to March 18th, 2020 were screened for inclusion. The following study characteristics were extracted independently, in single: Topic (General Info, Mechanism, Diagnosis, Transmission, Treatment, Prevention, Case Report, and Epidemic Forecasting), open access status (open access and subscription-based), continent of corresponding author (Asia, Australia, Africa, North America, South America, and Europe), tweets, and citations. A sign test was used to compare the tweet rate and citation rate per day. A negative binomial regression analysis was conducted to evaluate the association between tweet rate and study characteristics of interest. RESULTS 1328 studies were included in the analysis. Tweet rates were found to be significantly higher than citation rates for COVID-19 studies, with a median tweet rate of 1.09 (SD 156.95) tweets per day and median citation rate of 0.00 (SD 3.02) citations per day, resulting in a median of differences of 1.09 (95% CI 0.86-1.33, P < .001). 2018 journal impact factors were positively correlated with tweet rate (P < .001). The topics Diagnosis (P = .01), Transmission (P < .001), Treatment (P = .01), and Epidemic Forecasting (P < 0.001) were positively correlated with tweet rate, relative to Case Report. The following continents of the corresponding author were negatively correlated with tweet rate, Africa (P <.001), Australia (P = .03), and South America (P < .001), relative to Asia. Open access journals were negatively correlated with tweet rate, relative to subscription-based journals (P < .001). CONCLUSIONS COVID-19 studies had significantly higher tweets rates compared to citation rates. This study further identified study characteristics that are correlated with the dissemination of studies on Twitter, such as 2018 journal impact factor, continent of the corresponding author, topic of study, and open access status. This highlights the importance of altmetrics in periods of rapidly expanding research, such as the COVID-19 pandemic to localize highly disseminated articles.

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Analysis of the journal impact factor and related bibliometric indicators in education and educational research category

Education for Information ◽

10.3233/efi-200442 ◽

2021 ◽

pp. 1-22

Author(s):

Metin Orbay ◽

Orhan Karamustafaoğlu ◽

Ruben Miranda

Keyword(s):

Impact Factor ◽

Educational Research ◽

Journal Impact Factor ◽

Impact Factors ◽

Bibliometric Indicators ◽

Strongly Correlated ◽

Starting Point ◽

Consistent Assessment ◽

The Impact ◽

Journal Impact

This study analyzes the journal impact factor and related bibliometric indicators in Education and Educational Research (E&ER) category, highlighting the main differences among journal quartiles, using Web of Science (Social Sciences Citation Index, SSCI) as the data source. High impact journals (Q1) publish only slightly more papers than expected, which is different to other areas. The papers published in Q1 journal have greater average citations and lower uncitedness rates compared to other quartiles, although the differences among quartiles are lower than in other areas. The impact factor is only weakly negative correlated (r=-0.184) with the journal self-citation but strongly correlated with the citedness of the median journal paper (r= 0.864). Although this strong correlation exists, the impact factor is still far to be the perfect indicator for expected citations of a paper due to the high skewness of the citations distribution. This skewness was moderately correlated with the citations received by the most cited paper of the journal (r= 0.649) and the number of papers published by the journal (r= 0.484), but no important differences by journal quartiles were observed. In the period 2013–2018, the average journal impact factor in the E&ER has increased largely from 0.908 to 1.638, which is justified by the field growth but also by the increase in international collaboration and the share of papers published in open access. Despite their inherent limitations, the use of impact factors and related indicators is a starting point for introducing the use of bibliometric tools for objective and consistent assessment of researcher.

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