Abstract
Twitter, a popular microblogging platform, is at the epicenter of the social media explosion, with millions of users being able to create and publish short posts, referred to as tweets, in real time. The application of the OLAP (On-Line Analytical Processing) on large volumes of tweets is a challenge that would allow the extraction of information (especially knowledge) such as user behavior, new emerging issues, trends... In this paper, we pursue a goal of providing a generic multidimensional model dedicated to the OLAP of tweets. The proposed model reflects on some specifics such as recursive references between tweets and calculated attributes.