Discovering burst patterns of burst topic in Twitter

• Main Authors: DONG, Guozhong, YANG, Wu, ZHU, Feida, WANG, Wei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: Burst pattern; Burst topic; Frequent sub-graph mining; Hierarchical clustering; Databases and Information Systems; Numerical Analysis and Scientific Computing; Social Media
• Online Access: https://ink.library.smu.edu.sg/sis_research/3598; https://ink.library.smu.edu.sg/context/sis_research/article/4599/viewcontent/Discovering_burst_patterns_of_burst_topic_in_twitter.pdf
• Institution: Singapore Management University

Twitter has become one of largest social networks for users to broadcast burst topics. There have been many studies on how to detect burst topics. However, mining burst patterns in burst topics has not been solved by the existing works. In this paper, we investigate the problem of mining burst patte...