Sub-field normalization in the multiplicative case: High- and low-impact citation indicators

Herranz, Neus; Ruiz‐Castillo, Javier

doi:10.1093/reseval/rvs006

Cited by 14 publications

(9 citation statements)

References 31 publications

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“…In this way, results are obtained that are properly field normalized, like in the case of fractional counting, while at the same time publications are assigned fully to each co-author, like in the case of full counting. Multiplicative counting is used at the country level in a number of studies by Ruiz-Castillo and colleagues (e.g., Albarrán, Crespo, Ortuño, & Ruiz-Castillo, 2010;Herranz & Ruiz-Castillo, 2012a, 2012b. In our view, the disadvantage of multiplicative counting is that publications do not all have the same weight in the calculation of field-normalized indicators.…”

Section: Multiplicative Countingmentioning

confidence: 99%

Field-normalized citation impact indicators and the choice of an appropriate counting method

Waltman

Eck

2015

Journal of Informetrics

209

120

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Bibliometric studies often rely on field-normalized citation impact indicators in order to make comparisons between scientific fields. We discuss the connection between field normalization and the choice of a counting method for handling publications with multiple co-authors. Our focus is on the choice between full counting and fractional counting. Based on an extensive theoretical and empirical analysis, we argue that properly field-normalized results cannot be obtained when full counting is used.Fractional counting does provide results that are properly field normalized. We therefore recommend the use of fractional counting in bibliometric studies that require field normalization, especially in studies at the level of countries and research organizations. We also compare different variants of fractional counting. In general, it seems best to use either the author-level or the address-level variant of fractional counting.

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Section: Multiplicative Countingmentioning

confidence: 99%

Field-normalized citation impact indicators and the choice of an appropriate counting method

Waltman

Eck

2015

Journal of Informetrics

209

120

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“…Fortunately, previous results indicate that for many purposes journals assigned to a single or to several subject categories share similar characteristics, so that the strategy choice is not that crucial. Among other issues in citation analysis, the study of the skewness of citation distributions across fields at different aggregation levels, or the evaluation of the gap in citation impact between the U.S. and the European Union using different indicators, are very robust to the strategy selected (Herranz & Ruiz-Castillo, 2012a, 2012b, 2012c. All in all, in this paper we follow a multiplicative strategy.…”

Section: Ii1 Measurement Issuesmentioning

confidence: 99%

The skewness of scientific productivity

Ruiz‐Castillo

Costas

2014

Journal of Informetrics

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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. For productivity inequality, we use the coefficient of variation. To assess the skewness of productivity distributions we use a robust index of skeweness, 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 are 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.Acknowledgements. This is the third version of a Working Paper in this series with the same title whose second version appeared in May 2014. This paper was conceived while Ruiz-Castillo enjoyed the hospitality of the Centre for Science and Technology Studies, Leiden University, The Netherlands, during the 2013 spring term. Ruiz-Castillo also acknowledges financial help from the Spanish MEC through grant ECO2010-19596. The authors acknowledge fruitful conversations with Raquel Carrasco, as well as comments from the participants in a CWTS seminar. All remaining shortcomings are the sole responsibility of the authors.

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“…It can be argued that, from a normative point of view, this implication distorts the evaluation of research units in a given subfield. This is the additional reason why in their comparison of citation impact performance for three geographical areas (the United States, the European Union, and the rest of the world), Herranz and Ruiz‐Castillo (, , in press) also follow a multiplicative strategy.…”

Section: The Two Strategiesmentioning

confidence: 99%

Multiplicative and fractional strategies when journals are assigned to several subfields

Herranz

Ruiz‐Castillo

2012

J Am Soc Inf Sci Tec

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In many datasets, articles are classified into sub-fields through the journals in which they have been published. The problem is that many journals are assigned to a single sub-field, but many others are assigned to several sub-fields. This paper discusses a multiplicative and a fractional strategy to deal with this situation, and introduces a normalization procedure in the multiplicative case that takes into account differences in mean citation rates across sub-fields. The empirical part studies different aspects of citation distributions under the two strategies, namely: (i) the number of articles, (ii) the mean citation rate, (iii) the broad shape of the distribution, (iv) the characterization in terms of size-and scale-invariant indicators of high-and low-impact, and (v) the presence of extreme distributions, or distributions that behave very differently from the rest. It is found that, in spite of large differences in the number of articles according to both strategies, the similarity of the citation characteristics of articles published in journals assigned to one or several sub-fields guarantees that choosing one of the two strategies may not lead to a radically different picture in practical applications. Nevertheless, the evaluation of citation excellence through a high-impact indicator may considerably differ depending on that choice.

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Sub-field normalization in the multiplicative case: High- and low-impact citation indicators

Cited by 14 publications

References 31 publications

Field-normalized citation impact indicators and the choice of an appropriate counting method

Field-normalized citation impact indicators and the choice of an appropriate counting method

The skewness of scientific productivity

Multiplicative and fractional strategies when journals are assigned to several subfields

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