In the analysis of bibliometric networks, researchers often use mapping and clustering techniques in a combined fashion. Typically, however, mapping and clustering techniques that are used together rely on very different ideas and assumptions. We propose a unified approach to mapping and clustering of bibliometric networks. We show that the VOS mapping technique and a weighted and parameterized variant of modularity-based clustering can both be derived from the same underlying principle. We illustrate our proposed approach by producing a combined mapping and clustering of the most frequently cited publications that appeared in the field of information science in the period 1999-2008.

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. The comparison focuses on the methodological choices underlying the different 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.

The general aim of the article is to demonstrate how the results both of a structural analysis, and of a research performance assessment of a research field, can be enriched by combining elements of both into one integrated analysis. In addition, a procedure is discussed to select and analyse candidate benchmark institutes to assess the position of a particular research institute, in terms of both its cognitive orientation and its scientific production and impact at the international research front. The combined method is applied in an evaluation of the research scope and performance of the Inter‐university Centre for Micro‐Electronics (IMEC) in Leuven, Belgium. On the basis of the comments of an international panel of experts in micro‐electronics, the method was discussed in detail. We concluded that the method provides a detailed and useful picture of the position of the institute from an international perspective. Moreover, we found that the results of each of the two parts are an added value to the other.

A term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

In this paper we present the explorations of combining the two main pillars of evaluative bibliometrics. These two pillars, performance analysis and science mapping, both have their strengths and imperfections. In this study we show how these imperfections are dealt with by an integrated analysis.