Home

Beyond Trending Topics: Real-World Event Identification on Twitter

Hila Becker; Mor Naaman; Luis Gravano

Title:
Beyond Trending Topics: Real-World Event Identification on Twitter
Author(s):
Becker, Hila
Naaman, Mor
Gravano, Luis
Date:
Type:
Technical reports
Department:
Computer Science
Permanent URL:
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:
1191
Metadata:
text | xml

In Partnership with the Center for Digital Research and Scholarship at Columbia University Libraries/Information Services | Terms of Use