In this Master Thesis we have designed, implemented and evaluated a Web 2.0 platform for massive online-discussion, inspired by Innovation Jams. Innovation Jams, the original initiative from IBM, has proven to be successful at bringing together vast amounts of people, capturing their untapped knowledge and, while the participants are discussing, gather useful insights for a companyʼs innovation strategy [Spangler et al. 2006, Bjelland and Chapman Wood 2008]. Our approach, based in an open-source forum system, features visualization techniques and a recommender system in order to provide the participants in the Jam with useful insights and interesting discussion recommendations for an improved participation. A theoretical introduction and a state-of-the-art survey in recommender systems has been gathered in order to frame and support the design of the hybrid recommender system [Burke 2002], composed by a content-based and a collaborative filtering recommenders, developed for InnoJam.