Technical reports:
Beyond Trending Topics: Real-World Event Identification on Twitter
Hila Becker; Mor Naaman; Luis Gravano
Downloads:
- Title:
- Beyond Trending Topics: Real-World Event Identification on Twitter
- Author(s):
-
Becker, Hila
Naaman, Mor
Gravano, Luis - Date:
- 2011
- Type:
- Technical reports
- Department:
- Computer Science
- Permanent URL:
- http://hdl.handle.net/10022/AC:P:10668
- Series:
- Columbia University Computer Science Technical Reports
- Part Number:
- CUCS-012-11
- Publisher:
- Department of Computer Science, Columbia University
- Publisher Location:
- New York
- Abstract:
- User-contributed messages on social media sites such as Twitter have emerged as powerful, real-time means of information sharing on the Web. These short messages tend to reflect a variety of events in real time, earlier than other social media sites such as Flickr or YouTube, making Twitter particularly well suited as a source of real-time event content. In this paper, we explore approaches for analyzing the stream of Twitter messages to distinguish between messages about real-world events and non-event messages. Our approach relies on a rich family of aggregate statistics of topically similar message clusters, including temporal, social, topical, and Twitter-centric features. Our large-scale experiments over millions of Twitter messages show the effectiveness of our approach for surfacing real-world event content on Twitter.
- Subject(s):
- Computer science
- Item views:
- 903