Evaluating the Use of Social Networks in Author Name Disambiguation in Digital Libraries

Abstract

Digital libraries have become an important source of information for scientific communities. However, by gathering data from different sources, the problem of duplicate and ambiguous information about author names arises. Traditional methods of name disambiguation use syntactic attribute information.  However, recently the use of relationship networks has been studied in data deduplication. This article presents a study of the impact of adding social network analysis to traditional methods in the name disambiguation problem in digital libraries. Through experiments using subsets of real libraries, we show that the use of social network analysis significantly improves the quality of results.