News recommendation based on tweets for understanding of opinion variation and events

Online social networks (OSN) have become very popular in the last years. People use it to tell what they are thinking and feeling. As these OSN became bigger and its content propagation is fast, they are commonly used as personal-update mechanism. Sometimes, the quantity, variety and quality of information spread in OSN are a problem when a person tries to use this kind of system to keeping yourself updated. Aiming to find relevant news related to users' current interests or news that could explain an event, we present a recommender system based on Twitter.