Based on the foundation laid by the h-index we introduce and study the R-and AR-indices. These new indices eliminate some of the disadvantages of the h-index, especially when they are used in combination with the h-index. The R-index measures the h-core's citation intensity, while AR goes one step further and takes the age of publications into account. This allows for an index that can actually increase and decrease over time. We propose the pair (h, AR) as a meaningful indicator for research evaluation. We further prove a relation characterizing the h-index in the power law model. h-index, A-index, R-index, AR-index, g-index, performance evaluation, power law

Author cocitation analysis (ACA), a special type of cocitation analysis, was introduced by White and Griffith in 1981.This technique is used to analyze the intellectual structure of a given scientific field. In 1990, McCain published a technical overview that has been largely adopted as a standard. Here, McCain notes that Pearson's correlation coefficient (Pearson's r) is often used as a similarity measure in ACA and presents some advantages of its use. The present article criticizes the use of Pearson's r in ACA and sets forth two natural requirements that a similarity measure applied in ACA should satisfy. It is shown that Pearson's r does not satisfy these requirements. Real and hypothetical data are used in order to obtain counterexamples to both requirements. It is concluded that Pearson's r is probably not an optimal choice of a similarity measure in ACA. Still, further empirical research is needed to show if, and in that case to what extent, the use of similarity measures in ACA that fulfill these requirements would lead to objectively better results in full-scale studies. Further, problems related to incomplete cocitation matrices are discussed.

Social network analysis (SNA) is not a formal theory in sociology but rather a strategy for investigating social structures. As it is an idea that can be applied in many fields, we study, in particular, its influence in the information sciences. Information scientists study publication, citation and co-citation networks, collaboration structures and other forms of social interaction networks. Moreover, the Internet represents a social network of an unprecedented scale. In all these studies social network analysis can successfully be applied. SNA is further related to recent theories concerning the free market economy, geography and transport networks. The growth of SNA is documented and a co-author network of SNA is drawn. Centrality measures of the SNA network are calculated.