Abstract In a document network such as a citation network of scienti?c documents, web-logs, etc., the content produced by authors exhibits their interest in certain topics. In addition some authors in?uence other authors’ interests. In this work, we propose to model the in?uence of cited authors along with the interests of citing authors. Moreover, we hypothesize that apart from the citations present in documents, the context surrounding the citation mention provides extra topical information about the cited authors. However, associating terms in the context to the cited authors remains an open problem. We propose novel document generation schemes that incorporate the context while simultaneously modeling the interests of citing authors and in?uence of the cited authors. Our experiments show signi?cant improvements over baseline models for various evaluation criteria such as link prediction between document and cited author, and quantitatively explaining unseen text.