ABCal: a Python package for author bias computation and scientometric plotting for reviews and meta-analyses

Systematic reviews are critical summaries of the exiting literature on a given subject and, when combined with meta-analysis, provides a quantitative synthesis of evidence to direct and inform future research. Such reviews must, however, account for complex sources of between study heterogeneity and...

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Vydané v:Scientometrics Ročník 129; číslo 1; s. 581 - 600
Hlavný autor: Le Clercq, Louis-Stéphane
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Cham Springer International Publishing 01.01.2024
Springer Nature B.V
Springer Verlag
Predmet:
Authorship
Bias
Computation
Computer Science
Geographic distribution
Geographical distribution
Heterogeneity
Independent study
Information Storage and Retrieval
Library Science
Mathematics
Meta-analysis
Methods
Quantitative analysis
Scientometrics
Software
Systematic review
Writers
Plots
Reviews
Bias detection
Scientometric
Authorship
Author bias
Systematic
ISSN:0138-9130, 1588-2861
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Popis
Shrnutí:Systematic reviews are critical summaries of the exiting literature on a given subject and, when combined with meta-analysis, provides a quantitative synthesis of evidence to direct and inform future research. Such reviews must, however, account for complex sources of between study heterogeneity and possible sources of bias, such as publication bias. This paper presents the methods and results of a research study using a newly developed software tool called ABCal (version 1.0.2) to compute and assess author bias in the literature, providing a quantitative measure for the possible effect of overrepresented authors introducing bias to the overall interpretation of the literature. ABCal includes a new metric referred to as author bias, which is a measure of potential biases per paper when the frequency or proportions of contributions from specific authors are considered. The metric is able to account for a significant portion of the observed heterogeneity between studies included in meta-analyses. A meta-regression between observed effect measures and author bias values revealed that higher levels of author bias were associated with higher effect measures while lower author bias was evident for studies with lower effect measures. Furthermore, the software's capabilities to analyse authorship contributions and produce scientometric plots was able to reveal distinct patterns in both the temporal and geographic distributions of publications, which may relate to any evident publication bias. Thus, ABCal can aid researchers in gaining a deeper understanding of the research landscape and assist in identifying both key contributors and holistic research trends.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0138-9130
1588-2861
DOI:10.1007/s11192-023-04880-6