Centre for Science and Technology Studies

At the Centre for Science and Technology Studies (CWTS) of Leiden University, we have a standard set of bibliometric indicators that we use for research performance assessment purposes (Van Raan, 2005). We are currently working on a major revision of our indicators. In this abstract, we briefly discuss the new set of indicators that we are planning to adopt in the near future.

In this paper, we visualize the struc-ture and the evolution of the computational intelligence (CI) field. 1 Based on our visualizations, we analyze the way in which the CI field is divided into several subfields. The visualizations provide insight into the characteristics of each subfield and into the relations between the subfields. By comparing two visualizations, one based on data from 2002 and one based on data from 2006, we examine how the CI field has evolved over the last years.

Since the introduction of Scopus, there has been much debate on all aspects of such an ambitious competitor of Web of Science, which is often perceived as the 'golden standard'. One particular aspect that has been discussed is the journal classification scheme. Although not visible or useful for all users, this scheme plays an important role in the background of the database itself and for advanced users in bibliometrics.

In recent years, the use of bibliometric indicators has become more and more important on various levels in the Dutch science system, such as in national monitoring systems, in the research assessments of various disciplines and the research groups active therein, as well as within various types of research organizations, such as research institutes and universities. In most cases, bibliometrics is used for monitoring or evaluative purposes.

In this introductory chapter, I first give a motivation for probabilistic fuzzy systems (PFSs), which are the subject of study of this thesis. I also discuss the relevance of fuzzy systems in general and PFSs in particular to economic applications. I then formulate the research questions that are considered in the thesis. The chapter is concluded with an overview of the thesis. In this overview, the methodology that is adopted in the different parts of the thesis is also briefly discussed.

Abstract We present a mathematical analysis of the long-run behavior of genetic algorithms (GAs) that are used for modeling social phenomena. Our analysis relies on commonly used mathematical techniques in the field of evolutionary game theory. We make a number of assumptions in our analysis, the most important one being that the mutation rate is positive but infinitely small. Given our assumptions, we derive results that can be used to calculate the exact long-run behavior of a GA.

Abstract The last few years the field of taxonomy learning has become more and more important in computer science. However it also has relevance in economics, as it can be used for describing economic domains as finances, macroeconomics etc. There are numerous methods to create a taxonomy from the Web, corpus, or semantic lexicon. This thesis examines the different steps of the investigated methods dealing with the process of taxonomy learning.

Page 1. A general source-normalized approach to bibliometric research performance assessment Ludo Waltman and Nees Jan van Eck Centre for Science and Technology Studies, Leiden University STI 2010, Leiden, The Netherlands September 10, 2010 Page 2.

Various studies have shown the emergence of cooperative behavior in evolutionary models with spatially distributed agents. We investigate to what extent these findings generalize to evolutionary models of price competition among spatially distributed firms. We consider both one-and twodimensional models, and we vary the amount of information firms have about competitors in their neighborhood.

We study the dependence of the shape of the rank-frequency distribution g on the shape of the size-frequency distribution f and vice versa. We show mathematically that g is convexly decreasing if and only if f is monotonically decreasing and that g has an S-shape (ie, g is first convexly decreasing and then concavely decreasing) if and only if f is first increasing and then decreasing.

Page 1. Journal of Informetrics 4 (2010) 431–435 Contents lists available at ScienceDirect Journal of Informetrics journal homepage: www.elsevier.com/locate/joi Rivals for the crown: Reply to Opthof and Leydesdorff Anthony FJ van Raan∗, Thed N. van Leeuwen, Martijn S.

Abstract We are concerned with evolutionary algorithms that are employed for economic modeling purposes. We focus in particular on evolutionary algorithms that use a binary encoding of strategies. These algorithms, commonly referred to as genetic algorithms, are popular in agent-based computational economics research. In many studies, however, there is no clear reason for the use of a binary encoding of strategies.

Abstract In scientometric research, the use of cooccurrence data is very common. In many cases, a similarity measure is employed to normalize the data. However, there is no consensus among researchers on which similarity measure is most appropriate for normalization purposes. In this article, we theoretically analyze the properties of similarity measures for cooccurrence data, focusing in particular on four well-known measures: the association strength, the cosine, the inclusion index, and the Jaccard index.

In a recent paper, Egghe [Egghe, L.(in press). Mathematical derivation of the impact factor distribution. Journal of Informetrics] presents a mathematical analysis of the rank-order distribution of journal impact factors. The analysis is based on the central limit theorem. We criticize the empirical relevance of Egghe's analysis. More specifically, we argue that Egghe's analysis relies on an unrealistic assumption and we show that the analysis is not in agreement with empirical data.

Abstract We provide in this article a number of new insights into the methodological discussion about author co-citation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors' co-citation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine.

Abstract In this paper, we visualize the structure and the evolution of the computational intelligence (CI) field. Based on our visualizations, we analyze the way in which the CI field is divided into several subfields. The visualizations provide insight into the characteristics of each subfield and into the relations between the subfields. By comparing two visualizations, one based on data from 2002 and one based on data from 2006, we examine how the CI field has evolved over the last years.

Abstract A number of experimental studies have investigated whether cooperative behavior may emerge in multi-agent Q-learning. In some studies cooperative behavior did emerge, in others it did not. This paper provides a theoretical analysis of this issue. The analysis focuses on multi-agent Q-learning in iterated prisoner's dilemmas. It is shown that under certain assumptions cooperative behavior may emerge when multi-agent Q-learning is applied in an iterated prisoner's dilemma.

In the original papers by Alkemade et al.(2006, 2007), their evolutionary algorithms (EAs) exhibited an extreme degree of premature convergence when they were run according to approach I. This seemed a quite curious result. We are happy that the correction (Alkemade et al. 2008) makes clear that the degree of premature convergence is much lower than originally reported. There are three further comments that we would like to make on the work of Alkemade et al. First, Alkemade etal.

We propose a taxonomy of bibliometric indicators of scientific performance. The taxonomy relies on the property of consistency. The h-index is shown not to have this important property. Free Abstract We propose a taxonomy of bibliometric indicators of scientific performance. The taxonomy relies on the property of consistency. The h-index is shown not to have this important property.

Abstract In a recent article in JASIST, L. Leydesdorff and L. Vaughan (2006) asserted that raw cocitation data should be analyzed directly, without first applying a normalization such as the Pearson correlation. In this communication, it is argued that there is nothing wrong with the widely adopted practice of normalizing cocitation data.