The supplementary material, accessible online, is located at 101007/s11192-023-04675-9.
Prior research has examined the application of positive and negative language in academic discourse, revealing a preference for positive expressions in scholarly writing. However, a significant gap exists in our understanding of how linguistic positivity's traits and processes might differ depending on the particular academic area. Moreover, a more thorough investigation into the connection between positive language use and research impact is necessary. To investigate linguistic positivity in academic writing across disciplines, this study addressed these problems. Based on a 111-million-word dataset of research article abstracts collected from the Web of Science, this study investigated diachronic patterns of positive and negative language in eight academic fields, as well as the potential link between linguistic positivity and citation volume. The findings across the investigated academic fields reveal a pervasive increase in linguistic positivity. Hard disciplines exhibited a greater and more rapidly increasing degree of linguistic positivity in comparison to soft disciplines. JNJ-75276617 datasheet A positive association of notable significance was determined between citation counts and the degree of linguistic positivity. The temporal variations and disciplinary divergences of linguistic positivity were examined, and the ramifications for the scientific sphere were explored.
Highly influential journalistic contributions are frequently published in high-impact scientific journals, especially within the most current and active research areas. The meta-research analysis explored the publication records, influence, and declared conflicts of interest of non-research authors who had published more than 200 Scopus-indexed articles in highly regarded journals, including Nature, Science, PNAS, Cell, BMJ, Lancet, JAMA, or the New England Journal of Medicine. Out of a total of 154 prolific authors, 148 had published 67825 papers in their primary journal in a non-research context. These authors predominantly utilize Nature, Science, and BMJ as their publication platforms. Scopus reported that 35% of the examined journalistic publications were designated as full articles, and 11% as short surveys. Among the publications reviewed, 264 papers received citation counts greater than 100. The 2020-2022 period saw 40 of the top 41 most frequently cited papers focusing on the immediate and significant challenges presented by the COVID-19 pandemic. Consider the 25 extremely prolific authors, each publishing over 700 articles in a particular journal. A significant number of these authors achieved high citation counts (median of 2273 citations). Their research focus was overwhelmingly limited to their primary journal, resulting in minimal publication in other Scopus-indexed journals. Their influential work touched upon various pressing areas of study over many years. Three of the twenty-five participants held PhDs in diverse subject matters, and seven had attained a master's degree in journalism. Only the BMJ, on its website, provided disclosures of potential conflicts of interest for prolific science writers, but even then, only two of the twenty-five highly prolific authors revealed specific potential conflicts. Scrutinizing the assignment of considerable power to non-researchers in scientific discussions demands further consideration, and the disclosure of potential conflicts of interest necessitates a greater emphasis.
The internet era's concomitant surge in research output has highlighted the importance of retracting published scientific papers for the preservation of scientific integrity. Individuals have sought to improve their knowledge of the COVID-19 virus by increasing their engagement with scientific literature, creating a surge in interest among both the public and professional sectors since the pandemic began. To guarantee the articles met the inclusion criteria, the Retraction Watch Database COVID-19 blog was reviewed in June and November of 2022. A search of Google Scholar and Scopus was performed to obtain the citation count and SJR/CiteScore for each article. The average SJR of a journal publishing an article, in tandem with its CiteScore, was 1531 and 73 respectively. Averaging 448 citations, the retracted articles demonstrated a significantly higher citation rate than the average CiteScore (p=0.001). From June to November, a total of 728 new citations were garnered by retracted COVID-19 articles; the presence of 'withdrawn' or 'retracted' before the article title did not influence citation rates. Disregarding the COPE guidelines for retraction statements occurred in 32% of the assessed articles. We contend that retracted COVID-19 publications often presented bold, attention-grabbing claims that elicited a disproportionately high degree of interest within the scientific community. Beyond that, a substantial number of journals were not forthcoming with detailed explanations for retractions. Retractions, a potential catalyst for scientific discussion, currently fail to deliver the full story, presenting only the 'what' and not the 'why'.
Data sharing forms a cornerstone of open science (OS), and open data (OD) policies are being implemented more extensively by institutions and journals. OD's intent to augment academic influence and accelerate scientific exploration is noteworthy, but the strategy underlying this proposal requires more comprehensive discussion. The citation patterns of articles from Chinese economics journals are analyzed within this study to understand the subtle influence of OD policies.
Among Chinese social science journals, (CIE) is the first and only one to introduce a mandatory open data policy, obligating all published articles to share the original data and computational procedures. We leverage article-level data and a difference-in-differences (DID) approach to assess the comparative citation rates of papers published in CIE and 36 similar journals. The OD policy promptly increased the number of citations, resulting in an average increase of 0.25, 1.19, 0.86, and 0.44 more citations per article in the first four years following publication. The study's results further substantiated a considerable and persistent decrease in the citation benefits of the OD policy, turning negative five years after the publication. To conclude, this pattern of citation change reveals an OD policy's inherent duality: it can sharply increase citations but concurrently accelerate the obsolescence of scholarly articles.
The online version of the document offers supplementary materials; these can be found at 101007/s11192-023-04684-8.
The online version provides additional resources, found at 101007/s11192-023-04684-8.
Even with progress on gender equality issues in Australian science, the problem has not been completely resolved yet. The objective of this study was to gain a clearer understanding of gender disparities in Australian science, and it involved scrutinizing all first-authored articles from Australian researchers indexed in the Dimensions database, which were published between 2010 and 2020 and were gender-specific. The Field of Research (FoR) was utilized for classifying articles, and the Field Citation Ratio (FCR) was employed for evaluating citations. The years witnessed a growth in the ratio of female to male first authors across all fields of study, the sole exception being information and computing sciences. The study period showed an improvement in the ratio of articles authored solely by female researchers. JNJ-75276617 datasheet The Field Citation Ratio analysis suggests a citation advantage held by female researchers in several disciplines, encompassing mathematical sciences, chemical sciences, technology, built environment and design, studies of human society, law and legal studies, and studies in creative arts and writing. Female first-authored articles exhibited a higher average FCR than their male counterparts, a disparity that persisted even in fields like mathematical sciences, where male authors published more articles.
Institutions providing funding frequently solicit text-based research proposals to evaluate applicants. Analyzing the data within these documents can provide insights into the research supply available to institutions in their specific field. This paper describes a complete semi-supervised approach to document clustering, partially automating the categorization of research proposals based on their thematic areas of interest. JNJ-75276617 datasheet A three-step process underlies the methodology: first, manually annotating a document sample; second, clustering documents using a semi-supervised approach; and third, assessing cluster quality with quantitative metrics and expert evaluations of coherence, relevance, and distinctiveness. Detailed methodology is presented for facilitating replication, showcasing its application with real-world data. The US Army Telemedicine and Advanced Technology Research Center (TATRC) sought to organize submissions relating to technological innovations in military medicine, a process demonstrated in this categorization exercise. A comparative evaluation of methodological attributes was undertaken, encompassing unsupervised and semi-supervised clustering techniques, diverse document vectorization approaches, and various cluster outcome selection strategies. Outcomes demonstrate that pretrained Bidirectional Encoder Representations from Transformers (BERT) embeddings are preferable for this assignment, compared to the existing methods of text embedding. Expert assessments of clustering algorithms revealed that semi-supervised clustering produced coherence ratings that were approximately 25% better than standard unsupervised clustering, with insignificant variations in the distinctiveness of clusters. Evidently, the method of selecting cluster results, which aimed for a balance between internal and external validity, delivered the best possible outcomes. Through further refinement, this methodological framework shows promise as a useful analytical instrument to help institutions discover hidden knowledge within their unused archives and analogous administrative documentation.