Beyond Trending Topics: Real-World Event Identification on Twitter

Authors

  • Hila Becker Columbia University
  • Mor Naaman Rutgers University
  • Luis Gravano Columbia University

Abstract

User-contributed messages on social media sites such as Twitter have emerged aspowerful, real-time means of information sharing on the Web. These short messages tend to reflect a variety of events in real time, 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 andnon-event messages. Our approach relies on a rich family of aggregatestatistics of topically similar message clusters. Large-scale experiments over millions of Twitter messages show the effectiveness of our approach for surfacing real-world event content on Twitter.

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Published

2021-08-03

How to Cite

Becker, H., Naaman, M., & Gravano, L. (2021). Beyond Trending Topics: Real-World Event Identification on Twitter. Proceedings of the International AAAI Conference on Web and Social Media, 5(1), 438-441. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/14146