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23 Research products, page 1 of 3

  • Digital Humanities and Cultural Heritage
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  • 2017-2021
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  • English
  • Scientometrics

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  • Open Access English
    Authors: 
    Milad Haghani; Pegah Varamini;
    Publisher: Springer International Publishing
    Country: Australia
    Project: ARC | Discovery Early Career Re... (DE210101175)

    Following the outbreak of SARS-CoV-2 disease, within less than 8 months, the 50 years-old scholarly literature of coronaviruses grew to nearly three times larger than its size prior to 2020. Here, temporal evolution of the coronavirus literature over the last 30 years (N = 43,769) is analysed along with its subdomain of SARS-CoV-2 articles (N = 27,460) and the subdomain of reviews and meta-analytic studies (N = 1027). The analyses are conducted through the lenses of co-citation and bibliographic coupling of documents. (1) Of the N = 1204 review and meta-analytical articles of the coronavirus literature, nearly 88% have been published and indexed during the first 8 months of 2020, marking an unprecedented attention to reviews and meta-analyses in this domain, prompted by the SARS-CoV-2 pandemic. (2) The subset of 2020 SARS-CoV-2 articles is bibliographically distant from the rest of this literature published prior to 2020. Individual articles of the SARS-CoV-2 segment with a bridging role between the two bodies of articles (i.e., before and after 2020) are identifiable. (3) Furthermore, the degree of bibliographic coupling within the 2020 SARS-CoV-2 cluster is much poorer compared to the cluster of articles published prior to 2020. This could, in part, be explained by the higher diversity of topics that are studied in relation to SARS-CoV-2 compared to the literature of coronaviruses published prior to the SARS-CoV-2 disease. (4) The analyses on the subset of SARS-CoV-2 literature identified studies published prior to 2020 that have now proven highly instrumental in the development of various clusters of publications linked to SARS-CoV-2. In particular, the so-called “sleeping beauties” of the coronavirus literature with an awakening in 2020 were identified, i.e., previously published studies of this literature that had remained relatively unnoticed for several years but gained sudden traction in 2020 in the wake of the SARS-CoV-2 outbreak. This work documents the historical development of the literature on coronaviruses as an event-driven literature and as a domain that exhibited, arguably, the most exceptional case of publication burst in the history of science. It also demonstrates how scholarly efforts undertaken during peace time or prior to a disease outbreak could suddenly play a critical role in prevention and mitigation of health disasters caused by new diseases. Supplementary Information The online version contains supplementary material available at 10.1007/s11192-021-04036-4.

  • Open Access English
    Authors: 
    Adrian G. Barnett; Zoë A. Doubleday;
    Publisher: Netherlands : Springer
    Country: Australia
    Project: ARC | ARC Future Fellowships - ... (FT190100244)

    “COVID” which stands for corona virus disease, has become the world’s most infamous acronym. Previous analysis of acronyms in health and medical journals found a growing use of acronyms over time in titles and abstracts, with “DNA” as the most common. Here we examine acronyms in the pandemic year of 2020 to show the dramatic rise of COVID-related research. “COVID” was over five times more frequently used than “DNA” in 2020, and in just one year it has become the sixth most popular acronym of all time, surpassing “AIDS”, “PCR” and “MRI”. Refereed/Peer-reviewed

  • Open Access English
    Authors: 
    Bakthavachalam Elango;
    Publisher: Springer International Publishing

    The aim of the present study is to identify retracted articles in the biomedical literature (co) authored by Indian authors and to examine the features of retracted articles. The PubMed database was searched to find the retracted articles in order to reach the goal. The search yielded 508 records and retrieved for the detailed analysis of: authorships and collaboration type, funding information, who retracts? journals and impact factors, and reasons for retraction. The results show that most of the biomedical articles retracted were published after 2010 and common reasons are plagiarism and fake data for retraction. More than half of the retracted articles were co-authored within the institutions and there is no repeat offender. 25% of retracted articles were published in the top 15 journals and 33% were published in the non-impact factor journals. Average time from publication to retraction is calculated to 2.86 years and retractions due to fake data takes longest period among the reasons. Majority of the funded research was retracted due to fake data whereas it is plagiarism for non-funded.

  • Open Access English
    Authors: 
    Zhiqi Wang; Ronald Rousseau;
    Publisher: Springer International Publishing
    Country: Belgium

    Abstract: The Yule-Simpson paradox refers to the fact that outcomes of comparisons between groups are reversed when groups are combined. Using Essential Sciences Indicators, a part of InCites (Clarivate), data for countries, it is shown that although the Yule-Simpson phenomenon in citation analysis and research evaluation is not common, it isn't extremely rare either. The Yule-Simpson paradox is a phenomenon one should be aware of, otherwise one may encounter unforeseen surprises in scientometric studies.

  • Open Access English
    Authors: 
    Ozcan Saritas; Pavel Bakhtin; Ilya Kuzminov; Elena Khabirova;
    Publisher: Springer International Publishing

    Identifying and monitoring business and technological trends are crucial for innovation and competitiveness of businesses. Exponential growth of data across the world is invaluable for identifying emerging and evolving trends. On the other hand, the vast amount of data leads to information overload and can no longer be adequately processed without the use of automated methods of extraction, processing, and generation of knowledge. There is a growing need for information systems that would monitor and analyse data from heterogeneous and unstructured sources in order to enable timely and evidence-based decision-making. Recent advancements in computing and big data provide enormous opportunities for gathering evidence on future developments and emerging opportunities. The present study demonstrates the use of text-mining and semantic analysis of large amount of documents for investigating in business trends in mobile commerce (m-commerce). Particularly with the on-going COVID-19 pandemic and resultant social isolation, m-commerce has become a large technology and business domain with ever growing market potentials. Thus, our study begins with a review of global challenges, opportunities and trends in the development of m-commerce in the world. Next, the study identifies critical technologies and instruments for the full utilization of the potentials in the sector by using the intelligent big data analytics system based on in-depth natural language processing utilizing text-mining, machine learning, science bibliometry and technology analysis. The results generated by the system can be used to produce a comprehensive and objective web of interconnected technologies, trends, drivers and barriers to give an overview of the whole landscape of m-commerce in one business intelligence (BI) data mart diagram.

  • Open Access English
    Authors: 
    Shima Moradi; Sajedeh Abdi;
    Publisher: Springer International Publishing

    This commentary identifies and characterizes correction and erratum in COVID-19 publications with a scientometric approach by considering their rate of growth, reasons for correction, the time-span between publishing the original and corrected versions, as well as their citation status in four questions. It also suggestions to solve the current issues regarding indexing, retrieving, publishing, and research evaluation.

  • Open Access English
    Authors: 
    Stefano Mammola; Diego Fontaneto; Alejandro Martínez; Filipe Chichorro;
    Countries: Finland, Italy

    AbstractMany believe that the quality of a scientific publication is as good as the science it cites. However, quantifications of how features of reference lists affect citations remain sparse. We examined seven numerical characteristics of reference lists of 50,878 research articles published in 17 ecological journals between 1997 and 2017. Over this period, significant changes occurred in reference lists’ features. On average, more recent papers have longer reference lists and cite more high Impact Factor papers and fewer non-journal publications. We also show that highly cited articles across the ecological literature have longer reference lists, cite more recent and impactful references, and include more self-citations. Conversely, the proportion of ‘classic’ papers and non-journal publications cited, as well as the temporal span of the reference list, have no significant influence on articles’ citations. From this analysis, we distill a recipe for crafting impactful reference lists, at least in ecology.

  • Open Access English
    Authors: 
    Stan Benjamens; Vincent E de Meijer; Robert A. Pol; Martijn P D Haring;
    Publisher: Springer International Publishing
    Country: Netherlands

    The COVID-19 pandemic has vast global consequences. Yet, effective mitigation strategies and economic and medical outfall differ extensively across the globe. It is currently unclear how well researchers from all continents are represented in the unsolicited and solicited publications. A literature review was performed in SCOPUS on COVID-19 oriented publications in the four most impactful medical journals. These included the British Medical Journal, Journal of the American Medical Association, the New England Journal of Medicine and The Lancet. We identified 809 eligible publications out of identified 924 records. The vast majority of publications on COVID-19, in the four can be considered European (47.7%) or North-American (37.3%) research. Chinese reports were relatively common (8.8%); however, reports from other Asian countries (3.2%) were minimal. Research from the African (1.0%) and South-American continents (0.6%) was rarely published in these journals. These observations are not surprising, as they reflect global academic publishing. However, involving all continents into COVID-19 research is important as COVID-19 management strategies and societal and economic consequences differ extensively across the globe. We see an important role for medical journals in encouraging global voices through solicited articles, to ensure a weighted research and humanitarian response. Electronic supplementary material The online version of this article (10.1007/s11192-020-03730-z) contains supplementary material, which is available to authorized users.

  • Open Access English
    Authors: 
    Jaime A. Teixeira da Silva; Panagiotis Tsigaris; Mohammadamin Erfanmanesh;
    Publisher: Springer International Publishing

    The SARS-CoV-2 virus, which causes Covid-19, induced a global pandemic for which an effective cure, either in the form of a drug or vaccine, has yet to be discovered. In the few brief months that the world has known Covid-19, there has been an unprecedented volume of papers published related to this disease, either in a bid to find solutions, or to discuss applied or related aspects. Data from Clarivate Analytics' Web of Science, and Elsevier's Scopus, which do not index preprints, were assessed. Our estimates indicate that 23,634 unique documents, 9960 of which were in common to both databases, were published between January 1 and June 30, 2020. Publications include research articles, letters, editorials, notes and reviews. As one example, amongst the 21,542 documents in Scopus, 47.6% were research articles, 22.4% were letters, and the rest were reviews, editorials, notes and other. Based on both databases, the top three countries, ranked by volume of published papers, are the USA, China, and Italy while BMJ, Journal of Medical Virology and The Lancet published the largest number of Covid-19-related papers. This paper provides one snapshot of how the publishing landscape has evolved in the first six months of 2020 in response to this pandemic and discusses the risks associated with the speed of publications.

  • Open Access English
    Authors: 
    Andreas Rehs;
    Publisher: Universität Kassel

    AbstractThe detection of differences or similarities in large numbers of scientific publications is an open problem in scientometric research. In this paper we therefore develop and apply a machine learning approach based on structural topic modelling in combination with cosine similarity and a linear regression framework in order to identify differences in dissertation titles written at East and West German universities before and after German reunification. German reunification and its surrounding time period is used because it provides a structure with both minor and major differences in research topics that could be detected by our approach. Our dataset is based on dissertation titles in economics and business administration and chemistry from 1980 to 2010. We use university affiliation and year of the dissertation to train a structural topic model and then test the model on a set of unseen dissertation titles. Subsequently, we compare the resulting topic distribution of each title to every other title with cosine similarity. The cosine similarities and the regional and temporal origin of the dissertation titles they come from are then used in a linear regression approach. Our results on research topics in economics and business administration suggest substantial differences between East and West Germany before the reunification and a rapid conformation thereafter. In chemistry we observe minor differences between East and West before the reunification and a slightly increased similarity thereafter.