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1.
科学研究的目的在于创造知识,并应用理论成果解决我国社会、经济、文化等发展中的实际问题。将论文发表在国际期刊上可以让更多的国际同行了解我国最新的科研成果,为我国获得更多的国际影响力,所以在过去二十多年里SCI论文成为我国科研考核的一个重要指标。在这种科研评价导向下,我国学者发表的国际论文数量已居世界第一位,而大量来自国内同行的引用使得我国国际论文的被引量排名世界第二。本文提取1990至2015年Web of Science论文及其引文的数据,分析不同国家、不同学科在国家层次的自引情况,并在不同国家、不同学科之间进行比较。研究发现,在排除国内同行的自引后,我国国际论文的真实国际影响力仍然有限,除了临床医学和物理等少数学科外,其他学科仍然低于全球平均水平。  相似文献   

2.
The paper introduces a new journal impact measure called The Reference Return Ratio (3R). Unlike the traditional Journal Impact Factor (JIF), which is based on calculations of publications and citations, the new measure is based on calculations of bibliographic investments (references) and returns (citations). A comparative study of the two measures shows a strong relationship between the 3R and the JIF. Yet, the 3R appears to correct for citation habits, citation dynamics, and composition of document types – problems that typically are raised against the JIF. In addition, contrary to traditional impact measures, the 3R cannot be manipulated ad infinitum through journal self-citations.  相似文献   

3.
The ability to predict the long-term impact of a scientific article soon after its publication is of great value towards accurate assessment of research performance. In this work we test the hypothesis that good predictions of long-term citation counts can be obtained through a combination of a publication's early citations and the impact factor of the hosting journal. The test is performed on a corpus of 123,128 WoS publications authored by Italian scientists, using linear regression models. The average accuracy of the prediction is good for citation time windows above two years, decreases for lowly-cited publications, and varies across disciplines. As expected, the role of the impact factor in the combination becomes negligible after only two years from publication.  相似文献   

4.
Despite recent evidence that Microsoft Academic is an extensive source of citation counts for journal articles, it is not known if the same is true for academic books. This paper fills this gap by comparing citations to 16,463 books from 2013 to 2016 in the Book Citation Index (BKCI) against automatically extracted citations from Microsoft Academic and Google Books in 17 fields. About 60% of the BKCI books had records in Microsoft Academic, varying by year and field. Citation counts from Microsoft Academic were 1.5 to 3.6 times higher than from BKCI in nine subject areas across all years for books indexed by both. Microsoft Academic found more citations than BKCI because it indexes more scholarly publications and combines citations to different editions and chapters. In contrast, BKCI only found more citations than Microsoft Academic for books in three fields from 2013-2014. Microsoft Academic also found more citations than Google Books in six fields for all years. Thus, Microsoft Academic may be a useful source for the impact assessment of books when comprehensive coverage is not essential.  相似文献   

5.
The Journal Impact Factor (JIF) is linearly sensitive to self-citations because each self-citation adds to the numerator, whereas the denominator is not affected. Pinski and Narin (1976) Influence Weights (IW) are not or marginally sensitive to these outliers on the main diagonal of a citation matrix and thus provide an alternative to JIFs. Whereas the JIFs are based on raw citation counts normalized by the number of publications in the previous two years, IWs are based on the eigenvectors in the matrix of aggregated journal-journal citations without a reference to size: the cited and citing sides are normalized and combined by a matrix approach. Upon normalization, IWs emerge as a vector; after recursive multiplication of the normalized matrix, IWs can be considered a network measure of prestige among the journals in the (sub)graph under study. As a consequence, the self-citations are integrated at the field level and no longer disturb the analysis as outliers. In our opinion, this independence of the diagonal values is a very desirable property of a measure of quality or impact. As an example, we elaborate Price’s (1981b) matrix of aggregated citation among eight biochemistry journals in 1977. Routines for the computation of IWs are made available at http://www.leydesdorff.net/iw.  相似文献   

6.
It is widely believed that collaboration is advantageous in science, for example, with collaboratively written articles tending to attract more citations than solo articles and strong arguments for the value of interdisciplinary collaboration. Nevertheless, it is not known whether the same is true for research that produces books. This article tests whether co-authored scholarly monographs attract more citations than solo monographs using books published before 2011 from 30 categories in the Web of Science. The results show that solo monographs numerically dominate collaborative monographs, but give no evidence of a citation advantage for collaboration on monographs. In contrast, for nearly all these subjects (28 out of 30) there was a citation advantage for collaboratively produced journal articles. As a result, research managers and funders should not incentivise collaborative research in book-based subjects or in research that aims to produce monographs, but should allow the researchers themselves to freely decide whether to collaborate or not.  相似文献   

7.
Questionable publications have been accused of “greedy” practices; however, their influence on academia has not been gauged. Here, we probe the impact of questionable publications through a systematic and comprehensive analysis with various participants from academia and compare the results with those of their unaccused counterparts using billions of citation records, including liaisons, i.e., journals and publishers, and prosumers, i.e., authors. Questionable publications attribute publisher-level self-citations to their journals while limiting journal-level self-citations; yet, conventional journal-level metrics are unable to detect these publisher-level self-citations. We propose a hybrid journal-publisher metric for detecting self-favouring citations among QJs from publishers. Additionally, we demonstrate that the questionable publications were less disruptive and influential than their counterparts. Our findings indicate an inflated citation impact of suspicious academic publishers. The findings provide a basis for actionable policy-making against questionable publications.  相似文献   

8.
The normalized citation indicator may not be sufficiently reliable when a short citation time window is used, because the citation counts for recently published papers are not as reliable as those for papers published many years ago. In a limited time period, recent publications usually have insufficient time to accumulate citations and the citation counts of these publications are not sufficiently reliable to be used in the citation impact indicators. However, normalization methods themselves cannot solve this problem. To solve this problem, we introduce a weighting factor to the commonly used normalization indicator Category Normalized Citation Impact (CNCI) at the paper level. The weighting factor, which is calculated as the correlation coefficient between citation counts of papers in the given short citation window and those in the fixed long citation window, reflects the degree of reliability of the CNCI value of one paper. To verify the effect of the proposed weighted CNCI indicator, we compared the CNCI score and CNCI ranking of 500 universities before and after introducing the weighting factor. The results showed that although there was a strong positive correlation before and after the introduction of the weighting factor, some universities’ performance and rankings changed dramatically.  相似文献   

9.
Delayed recognition is a concept applied to articles that receive very few to no citations for a certain period of time following publication, before becoming actively cited. To determine whether such a time spent in relative obscurity had an effect on subsequent citation patterns, we selected articles that received no citations before the passage of ten full years since publication, investigated the subsequent yearly citations received over a period of 37 years and compared them with the citations received by a group of papers without such a latency period. Our study finds that papers with delayed recognition do not exhibit the typical early peak, then slow decline in citations, but that the vast majority enter decline immediately after their first – and often only – citation. Middling papers’ citations remain stable over their lifetime, whereas the more highly cited papers, some of which fall into the “sleeping beauty” subtype, show non-stop growth in citations received. Finally, papers published in different disciplines exhibit similar behavior and did not differ significantly.  相似文献   

10.
The citations to a set of academic articles are typically unevenly shared, with many articles attracting few citations and few attracting many. It is important to know more precisely how citations are distributed in order to help statistical analyses of citations, especially for sets of articles from a single discipline and a small range of years, as normally used for research evaluation. This article fits discrete versions of the power law, the lognormal distribution and the hooked power law to 20 different Scopus categories, using citations to articles published in 2004 and ignoring uncited articles. The results show that, despite its popularity, the power law is not a suitable model for collections of articles from a single subject and year, even for the purpose of estimating the slope of the tail of the citation data. Both the hooked power law and the lognormal distributions fit best for some subjects but neither is a universal optimal choice and parameter estimates for both seem to be unreliable. Hence only the hooked power law and discrete lognormal distributions should be considered for subject-and-year-based citation analysis in future and parameter estimates should always be interpreted cautiously.  相似文献   

11.
Despite citation counts from Google Scholar (GS), Web of Science (WoS), and Scopus being widely consulted by researchers and sometimes used in research evaluations, there is no recent or systematic evidence about the differences between them. In response, this paper investigates 2,448,055 citations to 2299 English-language highly-cited documents from 252 GS subject categories published in 2006, comparing GS, the WoS Core Collection, and Scopus. GS consistently found the largest percentage of citations across all areas (93%–96%), far ahead of Scopus (35%–77%) and WoS (27%–73%). GS found nearly all the WoS (95%) and Scopus (92%) citations. Most citations found only by GS were from non-journal sources (48%–65%), including theses, books, conference papers, and unpublished materials. Many were non-English (19%–38%), and they tended to be much less cited than citing sources that were also in Scopus or WoS. Despite the many unique GS citing sources, Spearman correlations between citation counts in GS and WoS or Scopus are high (0.78-0.99). They are lower in the Humanities, and lower between GS and WoS than between GS and Scopus. The results suggest that in all areas GS citation data is essentially a superset of WoS and Scopus, with substantial extra coverage.  相似文献   

12.
Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to the citation network setting, and show that there are authors who frequently cite recent papers that become highly-cited in the future; these authors are referred to as discoverers. We develop a method for early identification of highly-cited papers based on the early citations from discoverers. The results show that the identified discoverers have a consistent citing pattern over time, and the early citations from them can be used as a valuable indicator to predict the future citation counts of a paper. The discoverers themselves are potential future outstanding researchers as they receive more citations than average.  相似文献   

13.
This paper explores a possible approach to a research evaluation, by calculating the renown of authors of scientific papers. The evaluation is based on the citation analysis and its results should be close to a human viewpoint. The PageRank algorithm and its modifications were used for the evaluation of various types of citation networks. Our main research question was whether better evaluation results were based directly on an author network or on a publication network. Other issues concerned, for example, the determination of weights in the author network and the distribution of publication scores among their authors. The citation networks were extracted from the computer science domain in the ISI Web of Science database. The influence of self-citations was also explored. To find the best network for a research evaluation, the outputs of PageRank were compared with lists of prestigious awards in computer science such as the Turing and Codd award, ISI Highly Cited and ACM Fellows. Our experiments proved that the best ranking of authors was obtained by using a publication citation network from which self-citations were eliminated, and by distributing the same proportional parts of the publications’ values to their authors. The ranking can be used as a criterion for the financial support of research teams, for identifying leaders of such teams, etc.  相似文献   

14.
The findings of Bornmann, Leydesdorff, and Wang (2013b) revealed that the consideration of journal impact improves the prediction of long-term citation impact. This paper further explores the possibility of improving citation impact measurements on the base of a short citation window by the consideration of journal impact and other variables, such as the number of authors, the number of cited references, and the number of pages. The dataset contains 475,391 journal papers published in 1980 and indexed in Web of Science (WoS, Thomson Reuters), and all annual citation counts (from 1980 to 2010) for these papers. As an indicator of citation impact, we used percentiles of citations calculated using the approach of Hazen (1914). Our results show that citation impact measurement can really be improved: If factors generally influencing citation impact are considered in the statistical analysis, the explained variance in the long-term citation impact can be much increased. However, this increase is only visible when using the years shortly after publication but not when using later years.  相似文献   

15.
Studies on the relationship between the numbers of citations and downloads of scientific publications is beneficial for understanding the mechanism of citation patterns and research evaluation. However, seldom studies have considered directionality issues between downloads and citations or adopted a case-by-case time lag length between the download and citation time series of each individual publication. In this paper, we introduce the Granger-causal inference strategy to study the directionality between downloads and citations and set up the length of time lag between the time series for each case. By researching the publications on the Lancet, we find that publications have various directionality patterns, but highly cited publications tend to feature greater possibilities to have Granger causality. We apply a step-by-step manner to introduce the Granger-causal inference method to information science as four steps, namely conducting stationarity tests, determining time lag between time series, establishing cointegration test, and implementing Granger-causality inference. We hope that this method can be applied by future information scientists in their own research contexts.  相似文献   

16.
The general aim of this paper is to show the results of a study in which we combined bibliometric mapping and citation network analysis to investigate the process of creation and transfer of knowledge through scientific publications. The novelty of this approach is the combination of both methods. In this case we analyzed the citations to a very influential paper published in 1990 that contains, for the first time, the term Absorptive Capacity. A bibliometric map identified the terms and the theories associated with the term while two techniques from the citation network analysis recognized the main papers during 15 years. As a result we identified the articles that influenced the research for some time and linked them into a research tradition that can be considered the backbone of the “Absorptive Capacity Field”.  相似文献   

17.
自存档文章引用优势案例分析研究   总被引：2，自引：1，他引：1  
通过对自存档文章典型案例的引用情况进行分析研究,得出自存档文章存在引用优势的结论,并进一步对自存档文章引用优势的成因进行了分析,发现除了开放获取模式之外,先见优势、质量歧视、质量优势等因素都对自存档文章的引用优势做出了贡献。为了扩大研究影响和提高被引率,建议科学家应该积极将文章自存档。  相似文献   

18.
For comparisons of citation impacts across fields and over time, bibliometricians normalize the observed citation counts with reference to an expected citation value. Percentile-based approaches have been proposed as a non-parametric alternative to parametric central-tendency statistics. Percentiles are based on an ordered set of citation counts in a reference set, whereby the fraction of papers at or below the citation counts of a focal paper is used as an indicator for its relative citation impact in the set. In this study, we pursue two related objectives: (1) although different percentile-based approaches have been developed, an approach is hitherto missing that satisfies a number of criteria such as scaling of the percentile ranks from zero (all other papers perform better) to 100 (all other papers perform worse), and solving the problem with tied citation ranks unambiguously. We introduce a new citation-rank approach having these properties, namely P100; (2) we compare the reliability of P100 empirically with other percentile-based approaches, such as the approaches developed by the SCImago group, the Centre for Science and Technology Studies (CWTS), and Thomson Reuters (InCites), using all papers published in 1980 in Thomson Reuters Web of Science (WoS). How accurately can the different approaches predict the long-term citation impact in 2010 (in year 31) using citation impact measured in previous time windows (years 1–30)? The comparison of the approaches shows that the method used by InCites overestimates citation impact (because of using the highest percentile rank when papers are assigned to more than a single subject category) whereas the SCImago indicator shows higher power in predicting the long-term citation impact on the basis of citation rates in early years. Since the results show a disadvantage in this predictive ability for P100 against the other approaches, there is still room for further improvements.  相似文献   

19.
Do academic journals favor authors who share their institutional affiliation? To answer this question we examine citation counts, as a proxy for paper quality, for articles published in four leading international relations journals during the years 2000–2015. We compare citation counts for articles written by “in-group members” (authors affiliated with the journal’s publishing institution) versus “out-group members” (authors not affiliated with that institution). Articles written by in-group authors received 18% to 49% fewer Web of Science citations when published in their home journal (International Security or World Politics) vs. an unaffiliated journal, compared to out-group authors. These results are mainly driven by authors who received their PhDs from Harvard or MIT. The findings show evidence of a bias within some journals towards publishing papers by faculty from their home institution, at the expense of paper quality.  相似文献   

20.
We investigate the contributions of scientific software to library and information science (LIS) research using a sample of 572 English language articles published in 13 journals in 2008, 2011, 2014, and 2017. In particular, we examine the use and citation of software freely available for academic use in the LIS literature; we also explore the extent to which researchers follow software citation instructions provided by software developers. Twenty-seven percent of the LIS journal articles in our sample explicitly mention and use software. Yet although LIS researchers are becoming increasingly reliant on software that is freely available for academic use, many still fail to include formal citations of such software in their publications. We also find that a substantial proportion of researchers, when documenting software use, do not cite the software in the manner recommended by its developers.  相似文献   

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