Relational hyperevent models for the coevolution of coauthoring and citation networks

Interest in the network analysis of bibliographic data has increased significantly in recent years. Yet, appropriate statistical models for examining the full dynamics of scientific citation networks, connecting authors to the papers they write and papers to other papers they cite, are not available. Very few studies exist that have examined how the social network between co-authors and the citation network among the papers shape one another and co-evolve. In consequence, our understanding of scientific citation networks remains incomplete. In this paper we extend recently derived relational hyperevent models (RHEM) to the analysis of scientific networks, providing a general framework to model the multiple dependencies involved in the relation linking multiple authors to the papers they write, and papers to the multiple references they cite. We demonstrate the empirical value of our model in an analysis of publicly available data on a scientific network comprising millions of authors and papers and assess the relative strength of various effects explaining scientific production. We outline the implications of the model for the evaluation of scientific research.