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1.
This paper exploits a unique 2003–2011 large dataset, indexed by Thomson Reuters, consisting of 17.2 million disambiguated authors classified into 30 broad scientific fields, as well as the 48.2 million articles resulting from a multiplying strategy in which any article co-authored by two or more persons is wholly assigned as many times as necessary to each of them. The dataset is characterized by a large proportion of authors who have their oeuvre in several fields. We measure individual productivity in two ways that are uncorrelated: as the number of articles per person and as the mean citation per article per person in the 2003–2011 period. We analyze the shape of the two types of individual productivity distributions in each field using size- and scale-independent indicators. To assess the skewness of productivity distributions we use a robust index of skewness, as well as the Characteristic Scores and Scales approach. For productivity inequality, we use the coefficient of variation. In each field, we study two samples: the entire population, and what we call “successful authors”, namely, the subset of scientists whose productivity is above their field average. The main result is that, in spite of wide differences in production and citation practices across fields, the shape of field productivity distributions is very similar across fields. The parallelism of the results for the population as a whole and for the subset of successful authors, when productivity is measured as mean citation per article per person, reveals the fractal nature of the skewness of scientific productivity in this case. These results are essentially maintained when any article co-authored by two or more persons is fractionally assigned to each of them.  相似文献   

2.
Characteristic scores and scales (CSS) – a well-established scientometric tool for the study of citation counts – have been used to document a striking phenomenon that characterizes citation distributions at high levels of aggregation: irrespective of scientific field and citation window empirical studies find a persistent pattern whereby about 70% of scientific papers belong to the class of poorly cited papers, about 21% belong to the class of fairly cited papers, 6% to that of remarkably cited papers and 3% to the class of outstandingly cited papers. This article aims to advance the understanding of this remarkable result by examining it in the context of the lognormal distribution, a popular model used to describe citation counts across scientific fields. The article shows that the application of the CSS method to lognormal distributions provides a very good fit to the 70–21–6–3% empirical pattern provided these distributions are characterized by a standard deviation parameter in the range of about 0.8–1.3. The CSS pattern is essentially explainable as an epiphenomenon of the lognormal functional form and, more generally, as a consequence of the skewness of science which is manifest in heavy-tailed citation distributions.  相似文献   

3.
Using the dataset based on Thomson Reuters Scientific “Web of Science” the distributions of some well-known indicators, such as h-index and g-index, were investigated, and different citation behaviors across different scientific fields resulting from their field dependences were found. To develop a field-independent index, two scaling methods, based on average citation of subject category and journal, were used to normalize the citation received by each paper of a certain author. The distributions of the generalized h-indices in different fields were found to follow a lognormal function with mean and standard deviation of approximately ?0.8 and 0.8, respectively. A field-independent index fi-index was then proposed, and its distribution was found to satisfy a universal power-law function with scaling exponent α approaching 3.0. Both the power-law and the lognormal universality of the distributions verified the field independence of these indicators. However, deciding which of the scaling methods is the better one is necessary for the validation of the field-independent index.  相似文献   

4.
Author keywords for scientific literature are terms selected and created by authors. Although most studies have focused on how to apply author keywords to represent their research interests, little is known about the process of how authors select keywords. To fill this research gap, this study presents a pilot study on author keyword selection behavior. Our empirical results show that the average percentages of author keywords appearing in titles, abstracts, and both titles and abstracts are 31%, 52.1%, and 56.7%, respectively. Meanwhile, we find that keywords also appear in references and high-frequency keywords. The proportions of author-selected keywords appearing in the references and high-frequency keywords are 41.6% and 56.1%, respectively. In addition, keywords of papers written by core authors (productive authors) are found to appear less frequently in titles and abstracts in their papers than that of others, and appear more frequently in references and high-frequency keywords. The percentages of keywords appearing in titles and abstracts in scientific papers are negatively correlated with citation counts of papers. In contrast, the percentages of author keywords appearing in high-frequency keywords are positively associated with citation counts of papers.  相似文献   

5.
Altmetrics promise useful support for assessing the impact of scientific works, including beyond the scholarly community and with very limited citation windows. Unfortunately, altmetrics scores are currently available only for recent articles and cannot be used as covariates in predicting long term impact of publications. However, the study of their statistical properties is a subject of evident interest to scientometricians. Applying the same approaches used in the literature to assess the universality of citation distributions, the intention here is to test whether the universal distribution also holds for Mendeley readerships. Results of the analysis carried out on a sample of publications randomly extracted from the Web of Science confirm that readerships seem to share similar shapes across fields and can be rescaled to a common and universal form. Such rescaling results as not particularly effective on the right tails. In other regions, rescaling causes a good collapse of field specific distributions, even for very recent publications.  相似文献   

6.
《Journal of Informetrics》2019,13(2):738-750
An aspect of citation behavior, which has received longstanding attention in research, is how articles’ received citations evolve as time passes since their publication (i.e., citation ageing). Citation ageing has been studied mainly by the formulation and fit of mathematical models of diverse complexity. Commonly, these models restrict the shape of citation ageing functions and explicitly take into account factors known to influence citation ageing. An alternative—and less studied—approach is to estimate citation ageing functions using data-driven strategies. However, research following the latter approach has not been consistent in taking into account those factors known to influence citation ageing. In this article, we propose a model-free approach for estimating citation ageing functions which combines quantile regression with a non-parametric specification able to capture citation inflation. The proposed strategy allows taking into account field of research effects, impact level effects, citation inflation effects and skewness in the distribution of cites effects. To test our methodology, we collected a large dataset consisting of more than five million citations to 59,707 research articles spanning 12 dissimilar fields of research and, with this data in hand, tested the proposed strategy.  相似文献   

7.
We report characteristics of in-text citations in over five million full text articles from two large databases – the PubMed Central Open Access subset and Elsevier journals – as functions of time, textual progression, and scientific field. The purpose of this study is to understand the characteristics of in-text citations in a detailed way prior to pursuing other studies focused on answering more substantive research questions. As such, we have analyzed in-text citations in several ways and report many findings here. Perhaps most significantly, we find that there are large field-level differences that are reflected in position within the text, citation interval (or reference age), and citation counts of references. In general, the fields of Biomedical and Health Sciences, Life and Earth Sciences, and Physical Sciences and Engineering have similar reference distributions, although they vary in their specifics. The two remaining fields, Mathematics and Computer Science and Social Science and Humanities, have different reference distributions from the other three fields and between themselves. We also show that in all fields the numbers of sentences, references, and in-text mentions per article have increased over time, and that there are field-level and temporal differences in the numbers of in-text mentions per reference. A final finding is that references mentioned only once tend to be much more highly cited than those mentioned multiple times.  相似文献   

8.
The author order of multi-authored papers can reveal subtle patterns of scientific collaboration and provide insights on the nature of credit assignment among coauthors. This article proposes a sequence-based perspective on scientific collaboration. Using frequently occurring sequences as the unit of analysis, this study explores (1) what types of sequence patterns are most common in the scientific collaboration at the level of authors, institutions, U.S. states, and nations in Library and Information Science (LIS); and (2) the productivity (measured by number of papers) and influence (measured by citation counts) of different types of sequence patterns. Results show that (1) the productivity and influence approximately follow the power law for frequent sequences in the four levels of analysis; (2) the productivity and influence present a significant positive correlation among frequent sequences, and the strength of the correlation increases with the level of integration; (3) for author-level, institution-level, and state-level frequent sequences, short geographical distances between the authors usually co-present with high productivities, while long distances tend to co-occur with large citation counts; (4) for author-level frequent sequences, the pattern of “the more productive and prestigious authors ranking ahead” is the one with the highest productivity and the highest influence; however, in the rest of the levels of analysis, the pattern with the highest productivity and the highest influence is the one with “the less productive and prestigious institutions/states/nations ranking ahead.”  相似文献   

9.
We study an agent-based model for generating citation distributions in complex networks of scientific papers, where a fraction of citations is allotted according to the preferential attachment rule (rich get richer) and the remainder is allocated accidentally (purely at random, uniformly). Previously, we derived and analysed such a process in the context of describing individual authors, but now we apply it to scientific journals in computer and information sciences. Based on the large DBLP dataset as well as the CORE (Computing Research and Education Association of Australasia) journal ranking, we find that the impact of journals is correlated with the degree of accidentality of their citation distribution. Citations to impactful journals tend to be more preferential, while citations to lower-ranked journals are distributed in a more accidental manner. Further, applied fields of research such as artificial intelligence seem to be driven by a stronger preferential component – and hence have a higher degree of inequality – than the more theoretical ones, e.g., mathematics and computation theory.  相似文献   

10.
近五年来国外图书馆学情报学研究成果的文献计量分析   总被引：2，自引：0，他引：2  
本文对SSCI(《社会科学引文索引》)收录的国外近五年图书情报学的16种期刊共计4055篇文献进行计量分析,着重对此专业高产作者、主要研究成果的地域分布和机构分布、学科分布以及引文情况等进行分析研究,以期在科学量化指标基础上,揭示国外图书情报学的发展状况和研究特点。  相似文献   

11.
Articles are cited for different purposes and differentiating between reasons when counting citations may therefore give finer-grained citation count information. Although identifying and aggregating the individual reasons for each citation may be impractical, recording the number of citations that originate from different article sections might illuminate the general reasons behind a citation count (e.g., 110 citations = 10 Introduction citations + 100 Methods citations). To help investigate whether this could be a practical and universal solution, this article compares 19 million citations with DOIs from six different standard sections in 799,055 PubMed Central open access articles across 21 out of 22 fields. There are apparently non-systematic differences between fields in the most citing sections and the extent to which citations from one section overlap with citations from another, with some degree of overlap in most cases. Thus, at a science-wide level, section headings are partly unreliable indicators of citation context, even if they are more standard within individual fields. They may still be used within fields to help identify individual highly cited articles that have had one type of impact, especially methodological (Methods) or context setting (Introduction), but expert judgement is needed to validate the results.  相似文献   

12.
Modeling a century of citation distributions   总被引：1，自引：1，他引：0  
The prevalence of uncited papers or of highly cited papers, with respect to the bulk of publications, provides important clues as to the dynamics of scientific research. Using 25 million papers and 600 million references from the Web of Science over the 1900–2006 period, this paper proposes a simple model based on a random selection process to explain the “uncitedness” phenomenon and its decline over the years. We show that the proportion of cited papers is a function of (1) the number of articles available (the competing papers), (2) the number of citing papers and (3) the number of references they contain. Using uncitedness as a departure point, we demonstrate the utility of the stretched-exponential function and a form of the Tsallis q-exponential function to fit complete citation distributions over the 20th century. As opposed to simple power-law fits, for instance, both these approaches are shown to be empirically well-grounded and robust enough to better understand citation dynamics at the aggregate level. On the basis of these models, we provide quantitative evidence and provisional explanations for an important shift in citation practices around 1960. We also propose a revision of the “citation classic” category as a set of articles which is clearly distinguishable from the rest of the field.  相似文献   

13.
Constructing academic networks to explore intellectual structure realize academic community detection, which can promote scientific research innovation and discipline progress, constitutes an important research topic. In this study, tripartite citation is fused with co-citation and coupling relations as a way of weighting the strength of direct citations, and all-author tripartite citation networks were constructed due to the contributions of all authors to the resulting publications. For purpose of exploring the potential of the all-author exclusive and inclusive tripartite citation networks, gene editing is taken as a case study. The extensive experimental comparisons are conducted with the traditional author single-citation networks and first-author tripartite citation network in terms of network structure characteristics, identifying core scholars, and exploring intellectual structures. The following conclusions can be drawn as follows: our all-author tripartite citation networks are able to help identify the most influential scholars in the field of gene editing, and the intellectual structures from exclusive tripartite citation networks are optimal.  相似文献   

14.
The h-index of Scopus is used as an important and practical instrument in analyzing the scientific level of researchers. In this research, 6 effective items (including author’s order, quality of publication source, quality of citation source, type of citation, research scopes of the authors and the regular scope of citation source) were considered in order to increase the accuracy and equity of research and also the optimization of scientometrics. In order to find the actual impact of each item, a relation with a default coefficient was considered, and all effective items were presented after evaluating the influence of them on the desired coefficients. Here, the introduced effective factors were separately investigated for 20 Iranian authors who are randomly selected. The analysis of the results showed that by applying the effective factors, the h-index of authors was obtained on the basis of real and scientific criteria; thus, the mean of all effective factors is introduced as modified h-index. Among considered authors, the lowest reduction in h-index was 10.67% and the highest reduction was 37.25% (SD was 6.5). This reduction was obtained in comparison with their h-index of Scopus, and it demonstrates that the authors, who have less reduction in their h-index value, have more scientific and honest approach to research.  相似文献   

15.
Wide differences in publication and citation practices make impossible the direct comparison of raw citation counts across scientific disciplines. Recent research has studied new and traditional normalization procedures aimed at suppressing as much as possible these disproportions in citation numbers among scientific domains. Using the recently introduced IDCP (Inequality due to Differences in Citation Practices) method, this paper rigorously tests the performance of six cited-side normalization procedures based on the Thomson Reuters classification system consisting of 172 sub-fields. We use six yearly datasets from 1980 to 2004, with widely varying citation windows from the publication year to May 2011. The main findings are the following three. Firstly, as observed in previous research, within each year the shapes of sub-field citation distributions are strikingly similar. This paves the way for several normalization procedures to perform reasonably well in reducing the effect on citation inequality of differences in citation practices. Secondly, independently of the year of publication and the length of the citation window, the effect of such differences represents about 13% of total citation inequality. Thirdly, a recently introduced two-parameter normalization scheme outperforms the other normalization procedures over the entire period, reducing citation disproportions to a level very close to the minimum achievable given the data and the classification system. However, the traditional procedure of using sub-field mean citations as normalization factors yields also good results.  相似文献   

16.
《Journal of Informetrics》2019,13(2):515-539
Counting of number of papers, of citations and the h-index are the simplest bibliometric indices of the impact of research. We discuss some improvements. First, we replace citations with individual citations, fractionally shared among co-authors, to take into account that different papers and different fields have largely different average number of co-authors and of references. Next, we improve on citation counting applying the PageRank algorithm to citations among papers. Being time-ordered, this reduces to a weighted counting of citation descendants that we call PaperRank. We compute a related AuthorRank applying the PageRank algorithm to citations among authors. These metrics quantify the impact of an author or paper taking into account the impact of those authors that cite it. Finally, we show how self- and circular-citations can be eliminated by defining a closed market of Citation-coins. We apply these metrics to the InSpire database that covers fundamental physics, presenting results for papers, authors, journals, institutes, towns, countries for all-time and in recent time periods.  相似文献   

17.
The principle of a new type of impact measure was introduced recently, called the “Audience Factor” (AF). It is a variant of the journal impact factor where emitted citations are weighted inversely to the propensity to cite of the source. In the initial design, propensity was calculated using the average length of bibliography at the source level with two options: a journal-level average or a field-level average. This citing-side normalization controls for propensity to cite, the main determinant of impact factor variability across fields. The AF maintains the variability due to exports–imports of citations across field and to growth differences. It does not account for influence chains, powerful approaches taken in the wake of Pinski–Narin's influence weights. Here we introduce a robust variant of the audience factor, trying to combine the respective advantages of the two options for calculating bibliography lengths: the classification-free scheme when the bibliography length is calculated at the individual journal level, and the robustness and avoidance of ad hoc settings when the bibliography length is averaged at the field level. The variant proposed relies on the relative neighborhood of a citing journal, regarded as its micro-field and assumed to reflect the citation behavior in this area of science. The methodology adopted allows a large range of variation of the neighborhood, reflecting the local citation network, and partly alleviates the “cross-scale” normalization issue. Citing-side normalization is a general principle which may be extended to other citation counts.  相似文献   

18.
作者学术关系研究进展   总被引：1，自引：0，他引：1  
[目的/意义] 作者学术关系是指从知识交流的角度出发,作者与作者之间表现出来的某种学术联系。对作者学术关系的研究有利于发现作者之间研究的相关度、学术共同体和科学知识结构,促进知识交流和知识传播,对知识创新和国家知识体系的健全和发展具有重要意义。[方法/过程] 采用综合归纳的方法,从作者合作关系、作者引用关系和作者链接关系3个方面对国内外作者学术关系的研究现状进行梳理。[结果/结论] 国内外学者对作者合作关系、作者共被引关系及作者链接关系的研究趋于丰富,对作者互引关系、作者耦合关系的研究还有待提升;研究领域主要集中在图书情报学领域。未来对作者学术关系的研究方向为作者重名问题分析、大数据引文挖掘及作者学术关系的拓展研究等。  相似文献   

19.
介绍作者引用认同和作者引证形象的概念,提炼作者引用认同和作者引证形象的特征,并与传统的作者被引分析进行比较;从狭义和广义上介绍期刊引用认同和期刊引证形象的概念,构建期刊引用认同和期刊引证形象的指标体系;界定机构引用认同和机构引证形象的概念和特征;提出引用认同和引证形象的分析角度。  相似文献   

20.
The numerical-algorithmic procedures of fractional counting and field normalization are often mentioned as indispensable requirements for bibliometric analyses. Against the background of the increasing importance of statistics in bibliometrics, a multilevel Poisson regression model (level 1: publication, level 2: author) shows possible ways to consider fractional counting and field normalization in a statistical model (fractional counting I). However, due to the assumption of duplicate publications in the data set, the approach is not quite optimal. Therefore, a more advanced approach, a multilevel multiple membership model, is proposed that no longer provides for duplicates (fractional counting II). It is assumed that the citation impact can essentially be attributed to time-stable dispositions of researchers as authors who contribute with different fractions to the success of a publication’s citation. The two approaches are applied to bibliometric data for 254 scientists working in social science methodology. A major advantage of fractional counting II is that the results no longer depend on the type of fractional counting (e.g., equal weighting). Differences between authors in rankings are reproduced more clearly than on the basis of percentiles. In addition, the strong importance of field normalization is demonstrated; 60% of the citation variance is explained by field normalization.  相似文献   

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