Co-author Network Analysis in DBLP: Classifying Personal Names

Abstract

In this paper we describe how the co-author network, which is built from the bibliographic records, can be incorporated into the process of personal name language classification. The model is tested on the DBLP data set. The results show that the extension of the language classification process with the co-author network may help to refine the name language classification obtained from the author names considered independently. It may also lead to the discovery of dependencies between the elements of the co-author network, or participation of authors in scientific communities. © Springer-Verlag Berlin Heidelberg 2008.