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GEAM: A general and event-related aspects model for Twitter event detection

conference contribution
posted on 2013-11-18, 00:00 authored by Y You, Guangyan HuangGuangyan Huang, J Cao, E Chen, J He, Y Zhang, L Hu
Event detection on Twitter has become a promising research direction due to Twitter's popularity, up-to-date feature, free writing style and so on. Unfortunately, it's a challenge to analyze Twitter dataset for event detection, since the informal expressions of short messages comprise many abbreviations, Internet buzzwords, spelling mistakes, meaningless contents etc. Previous techniques proposed for Twitter event detection mainly focus on clustering bursty words related to the events, while ignoring that these words may not be easily interpreted to clear event descriptions. In this paper, we propose a General and Event-related Aspects Model (GEAM), a new topic model for event detection from Twitter that associates General topics and Event-related Aspects with events. We then introduce a collapsed Gibbs sampling algorithm to estimate the word distributions of General topics and Event-related Aspects in GEAM. Our experiments based on over 7 million tweets demonstrate that GEAM outperforms the state-of-the-art topic model in terms of both Precision and DERate (measuring Duplicated Events Rate detected). Particularly, GEAM can get better event representation by providing a 4-tuple (Time, Locations, Entities, Keywords) structure of the detected events. We show that GEAM not only can be used to effectively detect events but also can be used to analyze event trends. © 2013 Springer-Verlag.

History

Event

International Conference on Web Information Systems Engineering (14th : 2013 : Nanjing, China)

Volume

8181

Issue

Part 2

Series

Lecture Notes in Computer Science

Pagination

319 - 332

Publisher

Springer

Location

Nanjing, China

Place of publication

Berlin, Germany

Start date

2013-10-13

End date

2013-10-15

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783642411540

Language

eng

Publication classification

E Conference publication; E1.1 Full written paper - refereed

Copyright notice

2013, Springer

Editor/Contributor(s)

X Lin, Y Manolopoulos, D Srivastava, G Huang

Title of proceedings

Web Information Systems Engineering - WISE 2013

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