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Ludo Waltman

Publications and source records attributed to Ludo Waltman.

At least 55 records · Page 3Linked to original sources

A systematic empirical comparison of different approaches for normalizing citation impact indicators

We address the question how citation-based bibliometric indicators can best be normalized to ensure fair comparisons between publications from different scientific fields and different years. In a systematic large-scale empirical analysis, we compare a traditional normalization approach based on a field classification system with three source normalization approaches. We pay special attention to the selection of the publications included in the analysis. Publications in national scientific journals, popular scientific magazines, and trade magazines are not included. Unlike earlier studies, we use algorithmically constructed classification systems to evaluate the different normalization approaches. Our analysis shows that a source normalization approach based on the recently introduced idea of fractional citation counting does not perform well. Two other source normalization approaches generally outperform the classification-system-based normalization approach that we study. Our analysis therefore offers considerable support for the use of source-normalized bibliometric indicators.

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F1000 recommendations as a new data source for research evaluation: A comparison with citations

F1000 is a post-publication peer review service for biological and medical research. F1000 aims to recommend important publications in the biomedical literature, and from this perspective F1000 could be an interesting tool for research evaluation. By linking the complete database of F1000 recommendations to the Web of Science bibliographic database, we are able to make a comprehensive comparison between F1000 recommendations and citations. We find that about 2% of the publications in the biomedical literature receive at least one F1000 recommendation. Recommended publications on average receive 1.30 recommendations, and over 90% of the recommendations are given within half a year after a publication has appeared. There turns out to be a clear correlation between F1000 recommendations and citations. However, the correlation is relatively weak, at least weaker than the correlation between journal impact and citations. More research is needed to identify the main reasons for differences between recommendations and citations in assessing the impact of publications.

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Source normalized indicators of citation impact: An overview of different approaches and an empirical comparison

Different scientific fields have different citation practices. Citation-based bibliometric indicators need to normalize for such differences between fields in order to allow for meaningful between-field comparisons of citation impact. Traditionally, normalization for field differences has usually been done based on a field classification system. In this approach, each publication belongs to one or more fields and the citation impact of a publication is calculated relative to the other publications in the same field. Recently, the idea of source normalization was introduced, which offers an alternative approach to normalize for field differences. In this approach, normalization is done by looking at the referencing behavior of citing publications or citing journals. In this paper, we provide an overview of a number of source normalization approaches and we empirically compare these approaches with a traditional normalization approach based on a field classification system. We also pay attention to the issue of the selection of the journals to be included in a normalization for field differences. Our analysis indicates a number of problems of the traditional classification-system-based normalization approach, suggesting that source normalization approaches may yield more accurate results.

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Some modifications to the SNIP journal impact indicator

The SNIP (source normalized impact per paper) indicator is an indicator of the citation impact of scientific journals. The indicator, introduced by Henk Moed in 2010, is included in Elsevier's Scopus database. The SNIP indicator uses a source normalized approach to correct for differences in citation practices between scientific fields. The strength of this approach is that it does not require a field classification system in which the boundaries of fields are explicitly defined. In this paper, a number of modifications that will be made to the SNIP indicator are explained, and the advantages of the resulting revised SNIP indicator are pointed out. It is argued that the original SNIP indicator has some counterintuitive properties, and it is shown mathematically that the revised SNIP indicator does not have these properties. Empirically, the differences between the original SNIP indicator and the revised one turn out to be relatively small, although some systematic differences can be observed. Relations with other source normalized indicators proposed in the literature are discussed as well.

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An empirical analysis of the use of alphabetical authorship in scientific publishing

There are different ways in which the authors of a scientific publication can determine the order in which their names are listed. Sometimes author names are simply listed alphabetically. In other cases, authorship order is determined based on the contribution authors have made to a publication. Contribution-based authorship can facilitate proper credit assignment, for instance by giving most credits to the first author. In the case of alphabetical authorship, nothing can be inferred about the relative contribution made by the different authors of a publication. In this paper, we present an empirical analysis of the use of alphabetical authorship in scientific publishing. Our analysis covers all fields of science. We find that the use of alphabetical authorship is declining over time. In 2011, the authors of less than 4% of all publications intentionally chose to list their names alphabetically. The use of alphabetical authorship is most common in mathematics, economics (including finance), and high energy physics. Also, the use of alphabetical authorship is relatively more common in the case of publications with either a small or a large number of authors.

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On the calculation of percentile-based bibliometric indicators

A percentile-based bibliometric indicator is an indicator that values publications based on their position within the citation distribution of their field. The most straightforward percentile-based indicator is the proportion of frequently cited publications, for instance the proportion of publications that belong to the top 10% most frequently cited of their field. Recently, more complex percentile-based indicators were proposed. A difficulty in the calculation of percentile-based indicators is caused by the discrete nature of citation distributions combined with the presence of many publications with the same number of citations. We introduce an approach to calculating percentile-based indicators that deals with this difficulty in a more satisfactory way than earlier approaches suggested in the literature. We show in a formal mathematical framework that our approach leads to indicators that do not suffer from biases in favor of or against particular fields of science.

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Research collaboration and the expanding science grid: Measuring globalization processes worldwide

This paper applies a new model and analytical tool to measure and study contemporary globalization processes in collaborative science - a world in which scientists, scholars, technicians and engineers interact within a 'grid' of interconnected research sites and collaboration networks. The building blocks of our metrics are the cities where scientific research is conducted, as mentioned in author addresses on research publications. The unit of analysis is the geographical distance between those cities. In our macro-level trend analysis, covering the years 2000-2010, we observe that research collaboration distances have been increasing, while the share of collaborative contacts with foreign cities has leveled off. Collaboration distances and growth rates differ significantly between countries and between fields of science. The application of a distance metrics to compare and track these processes opens avenues for further studies, both at the meso-level and at the micro-level, into how research collaboration patterns and trends are driving and shaping the connectivity fabric of world science.

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A new methodology for constructing a publication-level classification system of science

Classifying journals or publications into research areas is an essential element of many bibliometric analyses. Classification usually takes place at the level of journals, where the Web of Science subject categories are the most popular classification system. However, journal-level classification systems have two important limitations: They offer only a limited amount of detail, and they have difficulties with multidisciplinary journals. To avoid these limitations, we introduce a new methodology for constructing classification systems at the level of individual publications. In the proposed methodology, publications are clustered into research areas based on citation relations. The methodology is able to deal with very large numbers of publications. We present an application in which a classification system is produced that includes almost ten million publications. Based on an extensive analysis of this classification system, we discuss the strengths and the limitations of the proposed methodology. Important strengths are the transparency and relative simplicity of the methodology and its fairly modest computing and memory requirements. The main limitation of the methodology is its exclusive reliance on direct citation relations between publications. The accuracy of the methodology can probably be increased by also taking into account other types of relations, for instance based on bibliographic coupling.

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The Leiden Ranking 2011/2012: Data collection, indicators, and interpretation

The Leiden Ranking 2011/2012 is a ranking of universities based on bibliometric indicators of publication output, citation impact, and scientific collaboration. The ranking includes 500 major universities from 41 different countries. This paper provides an extensive discussion of the Leiden Ranking 2011/2012. The ranking is compared with other global university rankings, in particular the Academic Ranking of World Universities (commonly known as the Shanghai Ranking) and the Times Higher Education World University Rankings. Also, a detailed description is offered of the data collection methodology of the Leiden Ranking 2011/2012 and of the indicators used in the ranking. Various innovations in the Leiden Ranking 2011/2012 are presented. These innovations include (1) an indicator based on counting a university's highly cited publications, (2) indicators based on fractional rather than full counting of collaborative publications, (3) the possibility of excluding non-English language publications, and (4) the use of stability intervals. Finally, some comments are made on the interpretation of the ranking, and a number of limitations of the ranking are pointed out.

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Text mining and visualization using VOSviewer

VOSviewer is a computer program for creating, visualizing, and exploring bibliometric maps of science. In this report, the new text mining functionality of VOSviewer is presented. A number of examples are given of applications in which VOSviewer is used for analyzing large amounts of text data.

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Universality of citation distributions revisited

Radicchi, Fortunato, and Castellano [arXiv:0806.0974, PNAS 105(45), 17268] claim that, apart from a scaling factor, all fields of science are characterized by the same citation distribution. We present a large-scale validation study of this universality-of-citation-distributions claim. Our analysis shows that claiming citation distributions to be universal for all fields of science is not warranted. Although many fields indeed seem to have fairly similar citation distributions, there are quite some exceptions as well. We also briefly discuss the consequences of our findings for the measurement of scientific impact using citation-based bibliometric indicators.

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The inconsistency of the h-index

The h-index is a popular bibliometric indicator for assessing individual scientists. We criticize the h-index from a theoretical point of view. We argue that for the purpose of measuring the overall scientific impact of a scientist (or some other unit of analysis) the h-index behaves in a counterintuitive way. In certain cases, the mechanism used by the h-index to aggregate publication and citation statistics into a single number leads to inconsistencies in the way in which scientists are ranked. Our conclusion is that the h-index cannot be considered an appropriate indicator of a scientist's overall scientific impact. Based on recent theoretical insights, we discuss what kind of indicators can be used as an alternative to the h-index. We pay special attention to the highly cited publications indicator. This indicator has a lot in common with the h-index, but unlike the h-index it does not produce inconsistent rankings.

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On the correlation between bibliometric indicators and peer review: Reply to Opthof and Leydesdorff

Opthof and Leydesdorff [arXiv:1102.2569] reanalyze data reported by Van Raan [arXiv:physics/0511206] and conclude that there is no significant correlation between on the one hand average citation scores measured using the CPP/FCSm indicator and on the other hand the quality judgment of peers. We point out that Opthof and Leydesdorff draw their conclusions based on a very limited amount of data. We also criticize the statistical methodology used by Opthof and Leydesdorff. Using a larger amount of data and a more appropriate statistical methodology, we do find a significant correlation between the CPP/FCSm indicator and peer judgment.

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A recursive field-normalized bibliometric performance indicator: An application to the field of library and information science

Two commonly used ideas in the development of citation-based research performance indicators are the idea of normalizing citation counts based on a field classification scheme and the idea of recursive citation weighing (like in PageRank-inspired indicators). We combine these two ideas in a single indicator, referred to as the recursive mean normalized citation score indicator, and we study the validity of this indicator. Our empirical analysis shows that the proposed indicator is highly sensitive to the field classification scheme that is used. The indicator also has a strong tendency to reinforce biases caused by the classification scheme. Based on these observations, we advise against the use of indicators in which the idea of normalization based on a field classification scheme and the idea of recursive citation weighing are combined.

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Globalisation of science in kilometres

The ongoing globalisation of science has undisputedly a major impact on how and where scientific research is being conducted nowadays. Yet, the big picture remains blurred. It is largely unknown where this process is heading, and at which rate. Which countries are leading or lagging? Many of its key features are difficult if not impossible to capture in measurements and comparative statistics. Our empirical study measures the extent and growth of scientific globalisation in terms of physical distances between co-authoring researchers. Our analysis, drawing on 21 million research publications across all countries and fields of science, reveals that contemporary science has globalised at a fairly steady rate during recent decades. The average collaboration distance per publication has increased from 334 kilometres in 1980 to 1553 in 2009. Despite significant differences in globalisation rates across countries and fields of science, we observe a pervasive process in motion, moving towards a truly interconnected global science system.

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The detection of "hot regions" in the geography of science: A visualization approach by using density maps

Spatial scientometrics has attracted a lot of attention in the very recent past. The visualization methods (density maps) presented in this paper allow for an analysis revealing regions of excellence around the world using computer programs that are freely available. Based on Scopus and Web of Science data, field-specific and field-overlapping scientific excellence can be identified in broader regions (worldwide or for a specific continent) where high quality papers (highly cited papers or papers published in Nature or Science) were published. We used a geographic information system to produce our density maps. We also briefly discuss the use of Google Earth.

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Towards a new crown indicator: An empirical analysis

We present an empirical comparison between two normalization mechanisms for citation-based indicators of research performance. These mechanisms aim to normalize citation counts for the field and the year in which a publication was published. One mechanism is applied in the current so-called crown indicator of our institute. The other mechanism is applied in the new crown indicator that our institute is planning to adopt. We find that at high aggregation levels, such as at the level of large research institutions or at the level of countries, the differences between the two mechanisms are very small. At lower aggregation levels, such as at the level of research groups or at the level of journals, the differences between the two mechanisms are somewhat larger. We pay special attention to the way in which recent publications are handled. These publications typically have very low citation counts and should therefore be handled with special care.

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Towards a new crown indicator: Some theoretical considerations

The crown indicator is a well-known bibliometric indicator of research performance developed by our institute. The indicator aims to normalize citation counts for differences among fields. We critically examine the theoretical basis of the normalization mechanism applied in the crown indicator. We also make a comparison with an alternative normalization mechanism. The alternative mechanism turns out to have more satisfactory properties than the mechanism applied in the crown indicator. In particular, the alternative mechanism has a so-called consistency property. The mechanism applied in the crown indicator lacks this important property. As a consequence of our findings, we are currently moving towards a new crown indicator, which relies on the alternative normalization mechanism.

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