An Epidemic Model for News Spreading on Twitter

被引：43
作者：
Abdullah, Saeed [1 ]
Wu, Xindong [1 ]
机构：
[1] Univ Vermont, Dept Comp Sci, Burlington, VT 05405 USA
来源：
2011 23RD IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2011) | 2011年
关键词：
D O I：
10.1109/ICTAI.2011.33
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we describe a novel approach to understand and explain news spreading dynamics on Twitter by using well-known epidemic models. Our underlying hypothesis is that the information diffusion on Twitter is analogous to the spread of a disease. As mathematical epidemiology has been extensively studied, being able to express news spreading as an epidemic model enables us to use a wide range of tools and procedures which have been proven to be both analytically rich and operationally useful. To further emphasize this point, we also show how we can readily use one of such tools - a procedure for detection of influenza epidemics, to detect change of trend dynamics on Twitter.
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页码：163 / 169
页数：7
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