The scientific impact of nations: journal placement and citation performance.
Ontology highlight
ABSTRACT:
SUBMITTER: Smith MJ
PROVIDER: S-EPMC4189927 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:This paper analyzes science productivity for nine developing countries. Results show that these nations are reducing their science gap, with R&D investments and scientific impact growing at more than double the rate of the developed world. But this "catching up" hides a very uneven picture among these nations, especially on what they are able to generate in terms of impact and output relative to their levels of investment and available resources. Moreover, unlike what one might expect, it is clear that the size of the nations and the relative scale of their R&D investments are not the key drivers of efficiency.
| S-EPMC4811426 | biostudies-literature
Project description:BackgroundSystematic reviews are important for informing clinical practice and health policy. The aim of this study was to examine the bibliometrics of systematic reviews and to determine the amount of variance in citations predicted by the journal impact factor (JIF) alone and combined with several other characteristics.MethodsWe conducted a bibliometric analysis of 1,261 systematic reviews published in 2008 and the citations to them in the Scopus database from 2008 to June 2012. Potential predictors of the citation impact of the reviews were examined using descriptive, univariate and multiple regression analysis.ResultsThe mean number of citations per review over four years was 26.5 (SD ± 29.9) or 6.6 citations per review per year. The mean JIF of the journals in which the reviews were published was 4.3 (SD ± 4.2). We found that 17% of the reviews accounted for 50% of the total citations and 1.6% of the reviews were not cited. The number of authors was correlated with the number of citations (r = 0.215, P < 0.001). Higher numbers of citations were associated with the following characteristics: first author from the United States (36.5 citations), an ICD-10 chapter heading of Neoplasms (31.8 citations), type of intervention classified as Investigation, Diagnostics or Screening (34.7 citations) and having an international collaboration (32.1 citations). The JIF alone explained more than half of the variation in citations (R(2) = 0.59) in univariate analysis. Adjusting for both JIF and type of intervention increased the R2 value to 0.81. Fourteen percent of reviews published in the top quartile of JIFs (? 5.16) received citations in the bottom quartile (eight or fewer), whereas 9% of reviews published in the lowest JIF quartile (? 2.06) received citations in the top quartile (34 or more). Six percent of reviews in journals with no JIF were also in the first quartile of citations.ConclusionsThe JIF predicted over half of the variation in citations to the systematic reviews. However, the distribution of citations was markedly skewed. Some reviews in journals with low JIFs were well-cited and others in higher JIF journals received relatively few citations; hence the JIF did not accurately represent the number of citations to individual systematic reviews.
| S-EPMC3847500 | biostudies-literature
Project description:Databases catalogue the corpus of research literature into scientific categories and report classes of bibliometric data such as the number of citations to articles, the number of authors, journals, funding agencies, institutes, references, etc. The number of articles and citations in a category are gauges of productivity and scientific impact but a quantitative basis to compare researchers between categories is limited. Here, we compile a list of bibliometric indicators for 236 science categories and citation rates of the 500 most cited articles of each category. The number of citations per paper vary by several orders of magnitude and are highest in multidisciplinary sciences, general internal medicine, and biochemistry and lowest in literature, poetry, and dance. A regression model demonstrates that citation rates to the top articles in each category increase with the square root of the number of articles in a category and decrease proportionately with the age of the references: articles in categories that cite recent research are also cited more frequently. The citation rate correlates positively with the number of funding agencies that finance the research. The category h-index correlates with the average number of cites to the top 500 ranked articles of each category ([Formula: see text]). Furthermore, only a few journals publish the top 500 cited articles in each category: four journals publish 60% ([Formula: see text]) of these and ten publish 81% ([Formula: see text]).
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Project description:Quantifying and comparing the scientific output of researchers has become critical for governments, funding agencies and universities. Comparison by reputation and direct assessment of contributions to the field is no longer possible, as the number of scientists increases and traditional definitions about scientific fields become blurred. The h-index is often used for comparing scientists, but has several well-documented shortcomings. In this paper, we introduce a new index for measuring and comparing the publication records of scientists: the pagerank-index (symbolised as π). The index uses a version of pagerank algorithm and the citation networks of papers in its computation, and is fundamentally different from the existing variants of h-index because it considers not only the number of citations but also the actual impact of each citation. We adapt two approaches to demonstrate the utility of the new index. Firstly, we use a simulation model of a community of authors, whereby we create various 'groups' of authors which are different from each other in inherent publication habits, to show that the pagerank-index is fairer than the existing indices in three distinct scenarios: (i) when authors try to 'massage' their index by publishing papers in low-quality outlets primarily to self-cite other papers (ii) when authors collaborate in large groups in order to obtain more authorships (iii) when authors spend most of their time in producing genuine but low quality publications that would massage their index. Secondly, we undertake two real world case studies: (i) the evolving author community of quantum game theory, as defined by Google Scholar (ii) a snapshot of the high energy physics (HEP) theory research community in arXiv. In both case studies, we find that the list of top authors vary very significantly when h-index and pagerank-index are used for comparison. We show that in both cases, authors who have collaborated in large groups and/or published less impactful papers tend to be comparatively favoured by the h-index, whereas the pagerank-index highlights authors who have made a relatively small number of definitive contributions, or written papers which served to highlight the link between diverse disciplines, or typically worked in smaller groups. Thus, we argue that the pagerank-index is an inherently fairer and more nuanced metric to quantify the publication records of scientists compared to existing measures.
| S-EPMC4545754 | biostudies-literature
Project description:We propose a new method to assess the merit of any set of scientific papers in a given field based on the citations they receive. Given a field and a citation impact indicator, such as the mean citation or the [Formula: see text]-index, the merit of a given set of [Formula: see text] articles is identified with the probability that a randomly drawn set of [Formula: see text] articles from a given pool of articles in that field has a lower citation impact according to the indicator in question. The method allows for comparisons between sets of articles of different sizes and fields. Using a dataset acquired from Thomson Scientific that contains the articles published in the periodical literature in the period 1998-2007, we show that the novel approach yields rankings of research units different from those obtained by a direct application of the mean citation or the [Formula: see text]-index.
| S-EPMC3496740 | biostudies-literature
Project description:Bibliometric indicators increasingly affect careers, funding, and reputation of individuals, their institutions and journals themselves. In contrast to author self-citations, little is known about kinetics of journal self-citations. Here we hypothesized that they may show a generalizable pattern within particular research fields or across multiple fields. We thus analyzed self-cites to 60 journals from three research fields (multidisciplinary sciences, parasitology, and information science). We also hypothesized that the kinetics of journal self-citations and citations received from other journals of the same publisher may differ from foreign citations. We analyzed the journals published the American Association for the Advancement of Science, Nature Publishing Group, and Editura Academiei Române. We found that although the kinetics of journal self-cites is generally faster compared to foreign cites, it shows some field-specific characteristics. Particularly in information science journals, the initial increase in a share of journal self-citations during post-publication year 0 was completely absent. Self-promoting journal self-citations of top-tier journals have rather indirect but negligible direct effects on bibliometric indicators, affecting just the immediacy index and marginally increasing the impact factor itself as long as the affected journals are well established in their fields. In contrast, other forms of journal self-citations and citation stacking may severely affect the impact factor, or other citation-based indices. We identified here a network consisting of three Romanian physics journals Proceedings of the Romanian Academy, Series A, Romanian Journal of Physics, and Romanian Reports in Physics, which displayed low to moderate ratio of journal self-citations, but which multiplied recently their impact factors, and were mutually responsible for 55.9%, 64.7% and 63.3% of citations within the impact factor calculation window to the three journals, respectively. They did not receive nearly any network self-cites prior impact factor calculation window, and their network self-cites decreased sharply after the impact factor calculation window. Journal self-citations and citation stacking requires increased attention and elimination from citation indices.
| S-EPMC4835057 | biostudies-literature
Project description:This article presents a practical roadmap for scholarly publishers to implement data citation in accordance with the Joint Declaration of Data Citation Principles (JDDCP), a synopsis and harmonization of the recommendations of major science policy bodies. It was developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP) project, an initiative of FORCE11.org and the NIH BioCADDIE program. The structure of the roadmap presented here follows the "life of a paper" workflow and includes the categories Pre-submission, Submission, Production, and Publication. The roadmap is intended to be publisher-agnostic so that all publishers can use this as a starting point when implementing JDDCP-compliant data citation. Authors reading this roadmap will also better know what to expect from publishers and how to enable their own data citations to gain maximum impact, as well as complying with what will become increasingly common funder mandates on data transparency.
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Project description:A key decision in scientific work is whether to build on novel or well-established ideas. Because exploiting new ideas is often harder than more conventional science, novel work can be especially dependent on interactions with colleagues, the training environment, and ready access to potential collaborators. Location may thus influence the tendency to pursue work that is close to the edge of the scientific frontier in the sense that it builds on recent ideas. We calculate for each nation its position relative to the edge of the scientific frontier by measuring its propensity to build on relatively new ideas in biomedical research. Text analysis of 20+ million publications shows that the United States and South Korea have the highest tendencies for novel science. China has become a leader in favoring newer ideas when working with basic science ideas and research tools, but is still slow to adopt new clinical ideas. Many locations remain far behind the leaders in terms of their tendency to work with novel ideas, indicating that the world is far from flat in this regard.
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Project description:A number of studies suggest that scientific papers with women in leading-author positions attract fewer citations than those with men in leading-author positions. We report the results of a matched case-control study of 1,269,542 papers in selected areas of medicine published between 2008 and 2014. We find that papers with female authors are, on average, cited between 6.5 and 12.6% less than papers with male authors. However, the standardized mean differences are very small, and the percentage overlaps between the distributions for male and female authors are extensive. Adjusting for self-citations, number of authors, international collaboration and journal prestige, we find near-identical per-paper citation impact for women and men in first and last author positions, with self-citations and journal prestige accounting for most of the small average differences. Our study demonstrates the importance of focusing greater attention on within-group variability and between-group overlap of distributions when interpreting and reporting results of gender-based comparisons of citation impact.
| S-EPMC6677534 | biostudies-literature
Project description:Many fields face an increasing prevalence of multi-authorship, and this poses challenges in assessing citation metrics. Here, we explore multiple citation indicators that address total impact (number of citations, Hirsch H index [H]), co-authorship adjustment (Schreiber Hm index [Hm]), and author order (total citations to papers as single; single or first; or single, first, or last author). We demonstrate the correlation patterns between these indicators across 84,116 scientists (those among the top 30,000 for impact in a single year [2013] in at least one of these indicators) and separately across 12 scientific fields. Correlation patterns vary across these 12 fields. In physics, total citations are highly negatively correlated with indicators of co-authorship adjustment and of author order, while in other sciences the negative correlation is seen only for total citation impact and citations to papers as single author. We propose a composite score that sums standardized values of these six log-transformed indicators. Of the 1,000 top-ranked scientists with the composite score, only 322 are in the top 1,000 based on total citations. Many Nobel laureates and other extremely influential scientists rank among the top-1,000 with the composite indicator, but would rank much lower based on total citations. Conversely, many of the top 1,000 authors on total citations have had no single/first/last-authored cited paper. More Nobel laureates of 2011-2015 are among the top authors when authors are ranked by the composite score than by total citations, H index, or Hm index; 40/47 of these laureates are among the top 30,000 by at least one of the six indicators. We also explore the sensitivity of indicators to self-citation and alphabetic ordering of authors in papers across different scientific fields. Multiple indicators and their composite may give a more comprehensive picture of impact, although no citation indicator, single or composite, can be expected to select all the best scientists.
| S-EPMC4930269 | biostudies-literature