A decade of research in Statistics: a topic model approach F. De Battisti, A. Ferrara and S. Salini Abstract In this paper the international statistical literature of the last thirteen years is analyzed. Our aim is to understand on one side what are the most common topics, on the other side, where they are more developed and by whom. We want also to know how the topics are interconnected and how they evolved. For this purpose we use Scopus as bibliometric database, in particular the papers published in 16 journals that are representative for the statistical literature. For the analysis, we apply Topic Model approach. Key words: probabilistic topic models, scientometrics, clustering, text mining 1 Introduction A bibliographic record, related to a product, is composed by different information: authors, year, source, publisher, keywords, abstract, citations and so on. The clas- sical bibliometric analyses deals with bibliometric measures and indexes. An al- ternative analysis perspective is the study of textual information. The idea is that documents are mixture of latent topics, where a topic is a probability distribution over words. In this paper we try to show how the statistical literature of the last ten years in the world can be described using topic models. One feasible way to conduct the analysis is to consider the whole collection of papers in the considered years and assess whether there are relevant topics. This process is not more than a clustering Francesca De Battisti DEMM, Universit´ a degli Studi di Milano, e-mail: francesca.debattisti@unimi.it Alfio Ferrara DI, Universit` a degli Studi di Milano, e-mail: alfio.ferrara@unimi.it Silvia Salini DEMM, Universit´ a degli Studi di Milano, e-mail: silvia.salini@unimi.it 1