Co-occurrence analysis of scientific documents in citation networks

Abstract

Citation pattern analysis is an important component for measuring research performance of the author. Co-citation analysis has been used as an effective method to find citation pattern analysis, but it does not take co-occurrence analysis among authors. A method to find co-occurrence analysis among authors is proposed in this work. Web of science citation data set is used for experimentation and parsing of this data, extracted first author name and CR link. The next step in the proposed model is to find first author co-occurrence frequency and followed by all author co-occurrence frequency. In this work applied network density, Triadic closure on co-citation graph. The proposed method provides the author-author co-relation, predicting, who is probably next co-author and author collaborate on community of authors.