Campbell, D., Tippett, C., Côté, G., Roberge, G., and Archambault, É. (2016). An approach for the condensed presentation of intuitive citation impact metrics which remain reliable with very few publications. In: I. Ràfols, J. Molas-Gallart, E. Castro-Martínez, & R. Woolley (Eds.). Proceedings of the 21st International Conference on Science and Technology Indicators, pp. 1229–1240, Valencia, Spain: Editorial Universitat Politècnica de València.
An approach for presenting citation data in a condensed and intuitive manner which will allow for their reliable interpretation by policy analysts even in cases where the number of peer-reviewed publications produced by a given entity remains small is presented. The approach is described using country level data in Agronomy & Agriculture (2004–2013), an area of specialisation for many developing countries with a small output size. Four citation impact metrics, and a synthesis graph that we call the distributional micro-charts of relative citation counts, are considered in building our “preferred” presentation layout. These metrics include two indicators that have long been used by Science-Metrix in its bibliometric reports, the Average of Relative Citations (ARC) and the percentage of publications in the 10% most cited publications in the database (HCP), as well as two newer metrics, the Median of Relative Citations (MRC) and the Relative Integration Score (RIS). The findings reveal that the proposed approach combining the MRC and HCP with the distributional micro-charts effectively allows to better qualify the citation impact of entities in terms of central location, density of the upper citation tail and overall distribution than Science-Metrix former approach based on the ARC and HCP. This is especially true of cases with small population sizes where a strong presence of outliers (denoted by strong HCP scores) can have a significant effect on the central location of the citation data when estimated with an average.
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