With the rise of social media channels such as Twitter –the most popular microblogging service– the control of what is said about entities –companies, people or products– online has been shifted from them to users and consumers. This has generated the necessity of monitoring the reputation of those entities online. In this context, it is only natural to witness a significant growth of demand for text mining software for Online Reputation Monitoring: automatic tools that help processing, understanding and aggregating large streams of facts and opinions about a company or individual. Despite the variety of Online Reputation Monitoring tools on the market, there is no standard evaluation framework yet –a widely accepted set of task definitions, evaluation measures and reusable test collections to tackle this problem. In fact, there is even no consensus on what the tasks carried out during the Online Reputation Monitoring process are, on which a system should minimize the effort of the user.