Online Reputation Management has recently become a fundamental aspect of Public Relations for organizations, personalities and entities in general. The very reason why the online dimension of reputation is now essential the fact that it is the biggest, richest and most updated source of information, opinions and attitudes around any entity it is the reason why a manual analysis of information streams in media and social networks is not viable. Automatic processing of online information crucially depends of the advancements in many research fields (data structures and algorithms for real time Natural Language Processing, Opinion Mining, Textual Synthesis, Novelty Detection and Recommendation, multimedia search, social network analysis, etc.) that, up to now, have paid little attention to the online reputation scenario. For instance, opinion mining has been focused on product reviews, and its results are not applicable to the (much more complex) problem of evaluating how the content of information streams in sial networks may affect the reputation of a company. The project aims towards the creation of a new generation of online reputation monitoring systems, able to understand, process, aggregate and synthesize, in real time, facts, opinions and attitudes around an entity, of presenting such information in multiple dimensions, and of interacting with reputation experts so that they can accomplish their task better and faster. Our research will go from fundamental problems such as textual similarity or data structures for real time Natural Language Processing to prototype validation with reputation experts. Besides algorithms and prototypes, we will also create and distribute test collections to evaluate all relevant technologies in the reputation management scenario.