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Corpus Colossal: A Bibliometric Analysis of Neuroscience Abstracts and Impact Factor.

ABSTRACT: A field's priorities are reflected by the contents of its high-impact journals. Researchers in turn may choose to pursue research objectives based on what is believed to be most highly valued by their peers. However, these assessments of the field's priorities are often subjective, owing to a lack of formal quantification of high-impact journals' contents. By compiling a corpus of abstracts from within the field neuroscience, I was able to analyze which terms had differential frequencies between 13 high-impact and 14 medium-impact journals. Approximately 50,000 neuroscience abstracts were analyzed over the years 2014-2018. Several broad trends emerged from the analysis of which terms were biased toward high-impact journals. Generally speaking, high-impact journals tended to feature: genetic studies, use of the latest and most sophisticated methods, examinations of the orbitofrontal cortex or amygdala, and/or use of human or non-mammalian subjects. Medium-impact journals tended to feature motor or cardiovascular studies, use of older methods, examinations of caudal brain regions, and/or rats as subjects. This approach also allowed for the comparison of high-impact bias among: brain regions, methods, neurotransmitters, study species, and broad themes within neuroscience. A systematic approach to the contents of high-impact journals offers the field an objective view of itself.

SUBMITTER: Kenkel WM

PROVIDER: S-EPMC6618901 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Corpus Colossal: A Bibliometric Analysis of Neuroscience Abstracts and Impact Factor.

Kenkel William M WM

Frontiers in integrative neuroscience 20190703

A field's priorities are reflected by the contents of its high-impact journals. Researchers in turn may choose to pursue research objectives based on what is believed to be most highly valued by their peers. However, these assessments of the field's priorities are often subjective, owing to a lack of formal quantification of high-impact journals' contents. By compiling a corpus of abstracts from within the field neuroscience, I was able to analyze which terms had differential frequencies between ...[more]

PMID: 31333423

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Project description:BackgroundJournal impact factor (IF) is the leading method of scholarly assessment in today's research world, influencing where scholars submit their research and where funders distribute their resources. COVID-19, one of the most serious health crises, resulted in an unprecedented surge of publications across all areas of knowledge. An important question is whether COVID-19 affected the gold standard of scholarly assessment.ObjectiveIn this paper, we aimed to comprehensively compare the productivity trends of COVID-19 and non-COVID-19 literature as well as track their evolution and scholarly impact across 3 consecutive calendar years.MethodsWe took as an example 6 high-impact medical journals (Annals of Internal Medicine [Annals], The British Medical Journal [The BMJ], Journal of the American Medical Association [JAMA], The Lancet, Nature Medicine [NatMed], and The New England Journal of Medicine [NEJM]) and searched the literature using the Web of Science database for manuscripts published between January 1, 2019, and December 31, 2021. To assess the effect of COVID-19 and non-COVID-19 literature in their scholarly impact, we calculated their annual IFs and percentage changes. Thereafter, we estimated the citation probability of COVID-19 and non-COVID-19 publications along with their rates of publication and citation by journal.ResultsA significant increase in IF change for manuscripts including COVID-19 published from 2019 to 2020 (P=.002; Annals: 283%; The BMJ: 199%; JAMA: 208%; The Lancet: 392%; NatMed: 111%; and NEJM: 196%) and to 2021 (P=.007; Annals: 41%; The BMJ: 90%; JAMA: 6%; The Lancet: 22%; NatMed: 53%; and NEJM: 72%) was seen, against non-COVID-19 ones. The likelihood of highly cited publications was significantly increased in COVID-19 manuscripts between 2019 and 2021 (Annals: z=3.4, P<.001; The BMJ: z=4.0, P<.001; JAMA: z=3.8, P<.001; The Lancet: z=3.5, P<.001; NatMed: z=5.2, P<.001; and NEJM: z=4.7, P<.001). The publication and citation rates of COVID-19 publications followed a positive trajectory, as opposed to non-COVID-19. The citation rate for COVID-19 publications peaked by the second quarter of 2020 while that of the publication rate approximately a year later.ConclusionsThe rapid surge of COVID-19 publications emphasized the capacity of scientific communities to respond against a global health emergency, yet inflated IFs create ambiguity as benchmark tools for assessing scholarly impact. The immediate implication is a loss in value of and trust in journal IFs as metrics of research and scientific rigor perceived by academia and society. Loss of confidence toward procedures employed by highly reputable publishers may incentivize authors to exploit the publication process by monopolizing their research on COVID-19 and encourage them to publish in journals of predatory behavior.

Project description:Background: It is beneficial to evaluate changes in neuroscience research field regarding research directions and topics over a defined period. Such information enables stakeholders to quickly identify the most influential research and incorporate latest evidence into research-informed education. To our knowledge, no study reported changes in neuroscience literature over the last decade. Therefore, the current study determined research terms with highest citation scores, compared publication shares of research areas and contributing countries in this field from 2006 to 2015 and identified the most productive journals. Methods: Data were extracted from Web of Science and Journal Citation Reports (JCR). Only articles and reviews published in journals classified under the JCR "Neurosciences" category over the period of interest were included. Title and abstract fields of each included publication were extracted and analyzed via VOSviewer to identify recurring terms with high relative citation scores. Two term maps were produced for publications over the study period to illustrate the extent of co-occurrence, and the impact of terms was evaluated based on their relative citation scores. To further describe the recent research priority or "hot spots," 10 terms with the highest relative citation scores were identified annually. In addition, by applying Bradford's law, we identified 10 journals being the most productive journals per annum over the survey period and evaluated their bilbiometric performances. Results: From 2006 to 2015, there were 47 terms involved in the annual lists of top 10 terms with highest relative citation scores. The most frequently recurring terms were autism (8), meta-analysis (7), functional connectivity (6), default mode network (4) and neuroimaging (4). Neuroscience research related to psychology and behavioral sciences showed an increase in publication share over the survey period, and China has become one of the major contributors to neuroscience research. Ten journals were frequently identified (≥8 years) as core journals within the survey period. Discussion: The landscape of neuroscience research has changed recently, and this paper provides contemporary overview for researchers and health care workers interested in this field's research and developments. Brain imaging and brain connectivity terms had high relative citation scores.

Project description:Background: It might be difficult for clinicians and scientists to identify comprehensively the major research topics given the large number of publications. A bibliometric report that identifies the most-cited articles within the body of the relevant literature may provide insight and guidance for readers toward scientific topics that are considered important for researchers and all relevant workers of academia. To our knowledge, there is a lack of an overall evaluation of the most-cited articles and hence of a comprehensive review of major research topics in neuroscience. The present study was therefore proposed to analyze and characterize the 100 most-cited articles in neuroscience. Methods: Based on data provided from Web of Science, the 100 most-cited articles relevant to neuroscience were identified and characterized. Information was extracted for each included article to assess for the publication year, journal published, impact factor, adjusted impact factor, citation count (total, normalized, and adjusted), reference list, authorship and article type. Results: The total citation count for the 100 most-cited articles ranged from 7,326 to 2,138 (mean 3087.0) and the normalized citation count ranged from 0.163 to 0.007 (mean 0.054). The majority of the 100 articles were research articles (67%) and published from 1996 to 2000 (30%). The author and journal with the largest share of these 100 articles were Stephen M. Smith (n = 6) and Science (n = 13) respectively. Among the 100 most-cited articles, 37 were interlinked via citations of one another, and they could be classified into five major topics, four of which were scientific topics, namely neurological disorders, prefrontal cortex/emotion/reward, brain network, and brain mapping. The remaining topic was methodology. Interestingly 41 out of 63 of the rest, non-interlinked articles could also be categorized under the above five topics. Adjusted journal impact factor among these 100 articles did not appear to be associated with the corresponding adjusted citation count. Conclusion: The current study compiles a comprehensive list and analysis of the 100 most-cited articles relevant to neuroscience that enables the comprehensive identification and recognition of the most important and relevant research topics concerned.

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Corpus Colossal: A Bibliometric Analysis of Neuroscience Abstracts and Impact Factor.

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Corpus Colossal: A Bibliometric Analysis of Neuroscience Abstracts and Impact Factor.

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