Users interact with online news in many ways, one of them being sharing content through online social networking sites such as Twitter. There is a small but important group of users that devote a substantial amount of efiort and care to this activity. These users monitor a large variety of sources on a topic or around a story, carefully select interesting ma-terial on this topic, and disseminate it to an interested au-dience ranging from thousands to millions. These users are news curators, and are the main subject of study of this pa-per. We adopt the perspective of a journalist or news editor who wants to discover news curators among the audience engaged with a news site. We look at the users who shared a news story on Twit- ter and attempt to identify news curators who may provide more information related to that story. In this paper we describe how to find this specific class of curators, which we refer to as news story curators. Hence, we proceed to compute a set of features for each user, and demonstrate that they can be used to automatically find relevant cura-tors among the audience of two large news organizations.