Acarp: Author-Centric Analysis of Research Papers

Scientific publications are an important kind of user-generated content, which contains not only high-quality content but also structures, e.g. citations. Scientific publication analysis has attracted much attention in both database and data mining research community. In this demonstration, we present a system, named as Acarp, for analyzing research papers in database community. The relationship between a research paper and the authors is analyzed based on a learning to rank model. Not only the content of the paper, but also the citation graph is used in the analysis. Acarp can not only guess authors for papers under double-blind reviewing, but also analyze the researchers’ continuity and diversity of research. This author-centric analysis could be interesting to researchers and be useful for further studying on double-blind reviewing process.