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The spontaneous behavior in extreme events: a clustering-based quantitative analysis
conference contribution
posted on 2013-12-01, 00:00 authored by N Shi, C Gao, Zili ZhangZili Zhang, L Zhong, J HuangSocial media records the pulse of social discourse and drives human behaviors in temporal and spatial dimensions, as well as the structural characteristics. These online contexts give us an opportunity to understand social perceptions of people in the context of certain events, and can help us improve disaster relief. Taking Twitter as data source, this paper quantitatively measures exogenous and endogenous social influences on collective behaviors in different events based on standard fluctuation scaling method. Different from existing studies utilizing manual keywords to denote events, we apply a clustering-based event analysis to identify the core event and its related episodes in a hashtag network. The statistical results show that exogenous factors drive the amount of information about an event and the endogenous factors play a major role in the propagation of hashtags.
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Advanced Data Mining and Applications. International Conference (9th : 2013 : Hangzhou, China)Volume
8346Issue
PART 1Pagination
336 - 347Publisher
SpringerLocation
Hangzhou, ChinaPlace of publication
Berlin, GermanyPublisher DOI
Start date
2013-12-14End date
2013-12-16ISSN
0302-9743eISSN
1611-3349ISBN-13
9783642539138Language
engPublication classification
E Conference publication; E1.1 Full written paper - refereedCopyright notice
2013, SpringerEditor/Contributor(s)
H Motoda, Z Wu, L Cao, O Zaiane, M Yao, W WangTitle of proceedings
ADMA 2013 : Lecture Notes in Artificial Intelligence : Proceedings of the 9th International Conference on Advanced Data Mining and ApplicationsUsage metrics
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