Résumé
Tweets exchanged over the Internet represent an important source of information, even if their characteristics make them dicult to analyze (a maximum of 140 characters, etc.). In this paper, we define a data warehouse model to analyze large volumes of tweets by proposing measures relevant in the context of knowledge discovery. The use of data warehouses as a tool for the storage and analysis of textual documents is not new but current measures are not well-suited to the specificities of the manipulated data. We also propose a new way for extracting the context of a concept in a hierarchy. Experiments carried out on real data underline the relevance of our proposal.