THE EXTENT OF MULTIDISCIPLINARY AUTHORSHIP OF ARTICLES ON SCIENTOMETRICS AND BIBLIOMETRICS IN BRAZIL

The publications in scientometrics and bibliometrics with Brazilian authorship expanded exponentially in the 1990-2006 period, reaching 13 times in the Web of Science database and 19.5 times in the Google Scholar database. This increase is rather superior to that of the total Brazilian scientific production in the same time period (5.6 times in the Web of Science). Some characteristics to be noticed in this rise are: 1) The total number of articles during this period was 197; in that, 78% were published in 57 Brazilian journals and 22% in 13 international journals. 2) The national and international articles averaged 4.3 and 5.9 citations/article, respectively; two journals stood out among these, the national Ciencia da Informacao (44 articles averaging 6.7 citations/article) and the international Scientometrics (32 articles averaging 6.2 citations/article). 3) The articles encompass an impressive participation of authors from areas other than information science; only one-fourth of the authors are bound to the information science field, the remaining ones being distributed among the areas of humanities/business administration, biology/biomedicine, health and hard sciences. The occurrence of adventitious authors at this level of multidisciplinarity is uncommon in science. However, the possible benefits of such patterns are not clear in view of a fragmented intercommunication among the authors, as noticed through the citations. The advantages of changing this trend and of using other scientometric and bibliometric databases, such as SciELO, to avoid an almost exclusive use of the Web of Science database, are discussed.

Concentric characterization and classification of complex network nodes: Application to an institutional collaboration network

Differently from theoretical scale-free networks, most real networks present multi-scale behavior, with nodes structured in different types of functional groups and communities. While the majority of approaches for classification of nodes in a complex network has relied on local measurements of the topology/connectivity around each node, valuable information about node functionality can be obtained by concentric (or hierarchical) measurements. This paper extends previous methodologies based on concentric measurements, by studying the possibility of using agglomerative clustering methods, in order to obtain a set of functional groups of nodes, considering particular institutional collaboration network nodes, including various known communities (departments of the University of Sao Paulo). Among the interesting obtained findings, we emphasize the scale-free nature of the network obtained, as well as identification of different patterns of authorship emerging from different areas (e.g. human and exact sciences). Another interesting result concerns the relatively uniform distribution of hubs along concentric levels, contrariwise to the non-uniform pattern found in theoretical scale-free networks such as the BA model. (C) 2008 Elsevier B.V. All rights reserved.