Adaptive Representations for Tracking Breaking News on Twitter
Journal: Research Repository UCD (University College Dublin)
Year: 2014

Twitter is often the most up-to-date source for find-ing and tracking breaking news stories. Therefore, there is considerable interest in developing filters for tweet streams in order to track and summarize stories. This is a non-trivial text analytics task as tweets are short, and standard text similarity metrics often fail as stories evolve over time. In this paper we examine the effective-ness of adaptive text similarity mechanisms for track-ing and summarizing breaking news stories. We evalu