Personalized activity streams: Sifting through the "river of news"

Abstract

Activity streams have emerged as a means to syndicate updates about a user or a group of users within a social network site or a set of sites. As the flood of updates becomes highly intensive and noisy, users are faced with a "needle in a haystack" challenge when they wish to read the news most interesting to them. In this work, we study activity stream personalization as a means of coping with this challenge. We experiment with an enterprise activity stream that includes status updates and news across a variety of social media applications. We examine an entity-based user profile and a stream-based profile across three dimensions: people, terms, and places, and provide a rich set of results through a user study that combines direct rating of the objects in the profile with rating of the news items it produces. © 2011 ACM.