DPBT: A System for Detecting Pacemakers in Burst Topics
Conference Proceeding Article
Influential users usually have a large number of followers and play an important role in the diffusion of burst topic. In this paper, pacemakers are defined as the influential users that promote topic diffusion in the early stages of burst topic. Traditional influential users detection approaches have largely ignored pacemakers in burst topics. To solve this problem, we present DPBT, a system that can detect pacemakers in burst topics. In DPBT, we construct burst topic user graph for each burst topic and propose a pacemakers detection algorithm to detect pacemakers in Twitter. The demonstration shows that DPBT is effective to detect pacemakers in burst topics, such that the historical detection results can effectively help to detect and predict burst topics in the early stages.
Databases and Information Systems
Data Management and Analytics
Proceedings of the 17th International conference on Web-Age Information Management
DONG, Guozhong; YANG, Wu; ZHU, Feida; and WANG, Wei.
DPBT: A System for Detecting Pacemakers in Burst Topics. (2016). Proceedings of the 17th International conference on Web-Age Information Management. 9659, 537-540. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3186
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