Abstract
As social media sites have emerged as power communication platform recent years, users share their opinions on these sites all day long. These wealthy user-generated data usually reflect real-world event. The goal of this work is to identify events from social streams. We proposed a new method which utilizes temporal bursts of keywords and their co-occurrence relationships to identify events for social streams. The experimental result shows the usefulness of our method.