Real-Time Predicting Bursting Hashtags on Twitter

被引：0

作者：

Kong, Shoubin ^{[1
]}

Mei, Qiaozhu ^{[2
]}

Feng, Ling ^{[1
]}

Zhao, Zhe ^{[2
]}

机构：

[1] Tsinghua Univ, Dept CS&T, Tsinghua Natl Lab Informat Sci & Technol, Beijing, Peoples R China

[2] Univ Michigan, Sch Informat, Ann Arbor, MI 48109 USA

来源：

WEB-AGE INFORMATION MANAGEMENT, WAIM 2014 | 2014年 / 8485卷

基金：

中国国家自然科学基金;

关键词：

hashtag; burst; real-time prediction;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A large number of hashtags are generated every day on Twitter. Only a few hashtags can become bursting topics. It is quite challenging to predict such bursting hashtags in real-time. In this paper, we provide the first definition of a bursting hashtag, and propose a solution to the real-time prediction problem of bursting hashtags. The experimental results show that the proposed method outperforms other related methods.

引用

页码：268 / 271

页数：4

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