Social event identification and ranking on flickr

Li, Xuefei, Cai, Hongyun, Huang, Zi, Yang, Yang and Zhou, Xiaofang (2014) Social event identification and ranking on flickr. World Wide Web, 18 5: 1219-1245. doi:10.1007/s11280-014-0295-z

Author Li, Xuefei
Cai, Hongyun
Huang, Zi
Yang, Yang
Zhou, Xiaofang
Title Social event identification and ranking on flickr
Journal name World Wide Web   Check publisher's open access policy
ISSN 1386-145X
Publication date 2014-06-10
Year available 2014
Sub-type Article (original research)
DOI 10.1007/s11280-014-0295-z
Open Access Status
Volume 18
Issue 5
Start page 1219
End page 1245
Total pages 27
Place of publication New York NY United States
Publisher Springer New York
Collection year 2015
Language eng
Abstract Effective event modeling allows accurate event identification and monitoring to enable timely response to emergencies occurring in various applications. Although event identification (or detection) has been extensively studied in the last decade, the triggering relationship among initial and subsequent events has not been well studied, which limits the understanding of event evolvements from both spatial and temporal dimensions. Furthermore, it is also useful to measure the impact of events to the public so that the important events can be first seen. In this paper, we propose to systematically study event modeling and ranking in a novel framework. A new method is introduced to effectively identify events by considering the spreading effect of event in the spatio-temporal space. To capture the triggering relationships among events, we adapt the self-exciting point process model by jointly considering event spatial, temporal and content similarities. As a step further, we define the event impact and estimate it via random walk based on the triggering relationships. Finally, events can be ranked at different time stamps. Extensive experimental results on real-life datasets demonstrate promising performance of our proposal in identifying, monitoring and ranking events.
Keyword Spatio-temporal
Event identification
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online ahead of print 10 Jun 2014

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
School of Information Technology and Electrical Engineering Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 1 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Tue, 21 Oct 2014, 01:29:44 EST by System User on behalf of School of Information Technol and Elec Engineering