TY - GEN
T1 - The spontaneous behavior in extreme events
T2 - 9th International Conference on Advanced Data Mining and Applications, ADMA 2013
AU - Shi, Ning
AU - Gao, Chao
AU - Zhang, Zili
AU - Zhong, Lu
AU - Huang, Jiajin
PY - 2013
Y1 - 2013
N2 - Social 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.
AB - Social 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.
UR - http://www.scopus.com/inward/record.url?scp=84893103548&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-53914-5_29
DO - 10.1007/978-3-642-53914-5_29
M3 - 会议稿件
AN - SCOPUS:84893103548
SN - 9783642539138
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 336
EP - 347
BT - Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings
Y2 - 14 December 2013 through 16 December 2013
ER -