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What drives citations of frontier application publications?

ABSTRACT: A large body of literature exists on analysis of citation and reviews of application of efficiency frontier. However, the reviews that assessed the determinants of citation counts did not focus on frontier applications. We contribute to the literature by identifying the drivers of citations of frontier application publications on Ghana. We employed two-part mixture modelling with inverse hyperbolic sine (IHS) transformation of the second part, which was found to be more appropriate than single equation IHS transformation modelling, for our data. Use of stochastic frontier analysis or data envelopment analysis did not drive citations counts. However, quality of journals in which frontier application studies were published and accessibility of the journals to readers, drive citation counts. Authors, institutions and funders of studies on frontier applications may consider these over collaborations, in seeking growth in citation counts.

SUBMITTER: Djokoto JG

PROVIDER: S-EPMC7658712 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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What drives citations of frontier application publications?

Djokoto Justice G JG Agyei-Henaku Kofi Aaron A-O KAA Afrane-Arthur Akua A AA Badu-Prah Charlotte C Gidiglo Ferguson K FK Srofenyoh Francis Y FY

Heliyon 20201107 11

A large body of literature exists on analysis of citation and reviews of application of efficiency frontier. However, the reviews that assessed the determinants of citation counts did not focus on frontier applications. We contribute to the literature by identifying the drivers of citations of frontier application publications on Ghana. We employed two-part mixture modelling with inverse hyperbolic sine (IHS) transformation of the second part, which was found to be more appropriate than single e ...[more]

PMID: 33210007

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Project description:BackgroundThe increasing prevalence of retracted publications in stem cell research presents significant challenges to scientific integrity. Although retraction notices are issued, retracted studies continue to be cited, facilitating the dissemination of unreliable findings. This study aimed to systematically explore the characteristics of retracted stem cell publications and evaluate the impact of retractions on subsequent citations.MethodsThis study was conducted following the PRISMA guidelines. A comprehensive search of Web of Science, Retraction Watch Database, and PubMed was conducted from their inception through July 25, 2024, to identify retracted stem cell publications. Characteristics including publication details, retraction reasons, and citation counts were extracted. To assess the impact of retraction on subsequent citations, we compared citation patterns between a random sample of retracted papers and matched non-retracted controls from identical journals and issues. Further analysis was conducted to determine whether papers citing retracted articles had an elevated risk of subsequent retraction. Descriptive statistics, chi-squared tests, t-tests, and Mann-Kendall tests were used for data analysis.ResultsThe systematic search identified 1421 records, with 517 publications meeting inclusion criteria. Temporal analysis revealed two significant trends: an increasing retraction rate that peaked at 0.84% in 2023 and a declining time-to-retraction (median: 30 months, interquartile range: 13-60; Mann-Kendall, tau = - 0.29; P < 0.001). Hospital-affiliated researchers from China contributed to 244 (47.2%) of retractions. Data and image flaws were identified in 360 (69.6%) of retractions. Among 472 Web of Science-indexed retracted publications, 366 (77.5%) accumulated 4884 post-retraction citations, with 114 (24.2%) receiving more citations post-retraction than pre-retraction. Analysis of a random subset of retracted articles (n = 53) demonstrated that only 14 (4.2%) out of 334 post-retraction citations referenced the retraction notice. Compared with 639 non-retracted control publications, retracted articles showed significantly lower post-retraction citation rates (mean rank: 291.32 vs. 351.08; P = 0.01). Moreover, papers citing retracted articles exhibited an 11-fold higher risk of subsequent retraction (odds ratio (OR): 11.09; 95% confidence interval (CI): 7.06-17.43).ConclusionsThis analysis reveals substantial research integrity challenges within stem cell research. These findings suggest the necessity for enhanced surveillance mechanisms and standardized protocols to identify and curtail the dissemination of flawed research.

Project description:BackgroundPublications regarding the 100 top-cited articles in a given discipline are common, but studies reporting the association between article topics and their citations are lacking. Whether or not reviews and original articles have a higher impact factor than case reports is a point for verification in this study. In addition, article topics that can be used for predicting citations have not been analyzed. Thus, this study aims to METHODS:: We searched PubMed Central and downloaded 100 top-cited abstracts in the journal Medicine (Baltimore) since 2011. Four article types and 7 topic categories (denoted by MeSH terms) were extracted from abstracts. Contributors to these 100 top-cited articles were analyzed. Social network analysis and Sankey diagram analysis were performed to identify influential article types and topic categories. MeSH terms were applied to predict the number of article citations. We then examined the prediction power with the correlation coefficients between MeSH weights and article citations.ResultsThe citation counts for the 100 articles ranged from 24 to 127, with an average of 39.1 citations. The most frequent article types were journal articles (82%) and comparative studies (10%), and the most frequent topics were epidemiology (48%) and blood and immunology (36%). The most productive countries were the United States (24%) and China (23%). The most cited article (PDID = 27258521) with a count of 135 was written by Dr Shang from Shandong Provincial Hospital Affiliated to Shandong University (China) in 2016. MeSH terms were evident in the prediction power of the number of article citations (correlation coefficients = 0.49, t = 5.62).ConclusionThe breakthrough was made by developing dashboards showing the overall concept of the 100 top-cited articles using the Sankey diagram. MeSH terms can be used for predicting article citations. Analyzing the 100 top-cited articles could help future academic pursuits and applications in other academic disciplines.

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What drives citations of frontier application publications?

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What drives citations of frontier application publications?

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