Temporal analysis of author ranking using citation-collaboration network

Abstract

Automated author ranking mechanism in a given research domain has key applications like automatic faculty selection in an institution, selection of outstanding researcher in a particular research domain, selection of domain experts for reviewing articles or project proposals, etc. The advantage of automated mechanism is that it is transparent and free from personal intervention. On the other hand, temporal analysis of author ranking has importance in the issues like selection of candidates for project grants, selection for life-time achievement awards, etc. This being an era of shared authorship in scientific articles, finding exact contribution of an author in a field is always a challenge. In our present work, we propose a modified pagerank-based author ranking algorithm that may identify the exact contribution of a researcher in terms coauthorship scores and paper citation scores in the research field he/she is working, and validate them using H-index, an already well accepted author ranking strategy, with the help of DBLP data set. In addition, we perform a comparative analysis of the change in author ranking for different part of author spectrum over time.