Title

DPBT: A System for Detecting Pacemakers in Burst Topics

Publication Type

Conference Proceeding Article

Publication Date

6-2016

Abstract

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.

Discipline

Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

Proceedings of the 17th International conference on Web-Age Information Management

Volume

9659

First Page

537

Last Page

540

ISBN

9783319399362

Publisher

Springer

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