  With the increasing size of digital libraries it has become a challenge to
identify author names correctly. The situation becomes more critical when
different persons share the same name (homonym problem) or when the names of
authors are presented in several different ways (synonym problem). This paper
focuses on homonym names in the computer science bibliography DBLP. The goal of
this study is to evaluate a method which uses co-authorship networks and
analyze the effect of common names on it. For this purpose we clustered the
publications of authors with the same name and measured the effectiveness of
the method against a gold standard of manually assigned DBLP records. The
results show that despite the good performance of implemented method for most
names, we should optimize for common names. Hence community detection was
employed to optimize the method. Results prove that the applied method improves
the performance for these names.
