On the quest for currencies of science: Field "exchange rates" for citations and Mendeley readership

PurposeThe introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields.Design/methodology/approachThe authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013).FindingsThere are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on “exchange rates (ERs)” for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results.Originality/valueThese findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition.Merit, Expertise and Measuremen

The influence of highly cited papers on field normalised indicators

Field normalised average citation indicators are widely used to compare countries, universities and research groups. The most common variant, the Mean Normalised Citation Score (MNCS), is known to be sensitive to individual highly cited articles but the extent to which this is true for a log-based alternative, the Mean Normalised Log Citation Score (MNLCS), is unknown. This article investigates country-level highly cited outliers for MNLCS and MNCS for all Scopus articles from 2013 and 2012. The results show that MNLCS is influenced by outliers, as measured by kurtosis, but at a much lower level than MNCS. The largest outliers were affected by the journal classifications, with the Science-Metrix scheme producing much weaker outliers than the internal Scopus scheme. The high Scopus outliers were mainly due to uncitable articles reducing the average in some humanities categories. Although outliers have a numerically small influence on the outcome for individual countries, changing indicator or classification scheme influences the results enough to affect policy conclusions drawn from them. Future field normalised calculations should therefore explicitly address the influence of outliers in their methods and reporting

Identification of research communities in cited and uncited publications using a co-authorship network

Patterns of co-authorship provide an effective means of probing the structures of research communities. In this paper, we use the CiteSpace social network tool and co-authorship data from the Web of Science to analyse two such types of community. The first type is based on the cited publications of a group of highly productive authors in a particular discipline, and the second on the uncited publications of those highly productive authors. These pairs of communities were generated for three different countries—the People’s Republic of China (PRC), the United Kingdom (UK) and the United States of America (USA)—and for four different disciplines (as denoted by Web of Science subject categories)—Chemistry Organic, Engineering Environmental, Economics, and Management. In the case of the UK and USA, the structures of the cited and uncited communities in each of the four disciplines were markedly different from each other; in the case of the PRC, conversely, the cited and uncited PRC communities had broadly similar structures that were characterised by large groups of connected authors. We suggest that this may arise from a greater degree of guest or honorary authorship in the PRC than in the UK or the USA

Constructing bibliometric networks: A comparison between full and fractional counting

Merit, Expertise and Measuremen

On the quest for currencies of science

PurposeThe introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields.Design/methodology/approachThe authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013).FindingsThere are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on “exchange rates (ERs)” for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results.Originality/valueThese findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition.Merit, Expertise and Measuremen

Sistemas de deteccion de tecnologias sanitarias nuevas y emergentes. El proyecto Sintesis, nuevas tecnologias.

Centro de Informacion y Documentacion Cientifica (CINDOC). C/Joaquin Costa, 22. 28002 Madrid. SPAIN / CINDOC - Centro de Informaciòn y Documentaciòn CientìficaSIGLEESSpai