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The skewness of science in 219 sub-fields and a number of aggregates

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Abstract

This paper studies evidence from Thomson Scientific (TS) about the citation process of 3.7 million articles published in the period 1998–2002 in 219 Web of Science (WoS) categories, or sub-fields. Reference and citation distributions have very different characteristics across sub-fields. However, when analyzed with the Characteristic Scores and Scales (CSS) technique, which is replication and scale invariant, the shape of these distributions over three broad categories of articles appears strikingly similar. Reference distributions are mildly skewed, but citation distributions with a 5-year citation window are highly skewed: the mean is 20 points above the median, while 9–10% of all articles in the upper tail account for about 44% of all citations. The aggregation of sub-fields into disciplines and fields according to several aggregation schemes preserve this feature of citation distributions. It should be noted that when we look into subsets of articles within the lower and upper tails of citation distributions the universality partially breaks down. On the other hand, for 140 of the 219 sub-fields the existence of a power law cannot be rejected. However, contrary to what is generally believed, at the sub-field level the scaling parameter is above 3.5 most of the time, and power laws are relatively small: on average, they represent 2% of all articles and account for 13.5% of all citations. The results of the aggregation into disciplines and fields reveal that power law algebra is a subtle phenomenon.

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Notes

  1. Under the same restrictive hypothesis, Schubert and Glänzel (2007) and Glänzel (2007b, 2008) deduce the scaling parameter from an equation relating the h-index and the parameters of the assumed power law.

  2. The vast majority of articles written in citation analysis deal exclusively with citations received. For an exception, apart from Price’s (1965) seminal contribution and Albarrán and Ruiz-Castillo (2011), see Liang and Rousseau (2010) and the references quoted there.

  3. Recall that references are made to many different items: articles in TS-indexed journals, as well as articles in conference volumes, books, and other documents, none of them covered by TS. Moreover, some references are to articles published in TS journals before 1998 and, hence, outside our dataset.

  4. It is important to emphasize that these results coincide with those obtained in Albarrán and Ruiz-Castillo (2011) when analyzing reference and citation distributions using the original dataset in which each article is assigned by TS to only one of 22 broad fields.

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Acknowledgments

The authors acknowledge financial support from the Spanish MEC through grants SEJ2007-63098, SEJ2007-67436, ECO2009-11165, and ECO2010-19596. The database of Thomson Scientific (formerly Thomson-ISI; Institute for Scientific Information) has been acquired with funds from Santander Universities Global Division of Banco Santander. This paper is part of the SCIFI-GLOW Collaborative Project supported by the European Commission’s Seventh Research Framework Programme, CoSSH7-CT-2008-217436, and was presented in a Poster Session of the STI Conference held in Leiden, 9-11 September, 2010. References and suggestions by a referee led to an improved version of the paper.

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Authors and Affiliations

  1. Departamento de Fundamentos del Análisis Económico, Universidad de Alicante, Alicante, Spain

    Pedro Albarrán

  2. Departamento de Economía Cuantitativa, Universidad Autónoma de Madrid, Madrid, Spain

    Juan A. Crespo

  3. Departamento de Economía, Universidad Carlos III, Madrid, Spain

    Ignacio Ortuño

  4. Departamento de Economía, Universidad Carlos III & Research Associate of the CEPR Project SCIFI-GLOW, Madrid, Spain

    Javier Ruiz-Castillo

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  1. Pedro Albarrán
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  2. Juan A. Crespo
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  3. Ignacio Ortuño
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  4. Javier Ruiz-Castillo
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Correspondence to Javier Ruiz-Castillo.

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Albarrán, P., Crespo, J.A., Ortuño, I. et al. The skewness of science in 219 sub-fields and a number of aggregates. Scientometrics 88, 385–397 (2011). https://doi.org/10.1007/s11192-011-0407-9

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