Event Recommendation using Twitter Activity

Abstract

User interactions with Twitter (social network) frequently take place on mobile devices - a user base that it strongly caters to. As much of Twitter's traffic comes with geo-tagging information associated with it, it is a natural platform for geographic recommendations. This paper proposes an event recommender system for Twitter users, which identifies twitter activity co-located with previous events, and uses it to drive geographic recommendations via item-based collaborative filtering.