"Online burst events detection oriented real-time microblog message str" by Guozhong DONG, Jun GAO et al.
 

Publication Type

Journal Article

Version

publishedVersion

Publication Date

1-2019

Abstract

The rapid spread of microblog messages and sensitivity of unexpected events make microblog become the public opinion center of burst events. Online burst events detection oriented real-time microblog message stream has become an important research problem in the field of microblog public opinion. Because of the large amount of real-time microblog message stream and irregular language of microblog message, it is important to process real-time microblog message stream and detect burst events accurately. In this paper, an online burst events detection framework is proposed. In this framework, abnormal messages are detected based on sliding time window and two-level hash table. Combined with event features, an online incremental clustering algorithm is used to cluster abnormal messages and detect burst events. Experimental results in the real-time microblog message stream environment show that our framework can be used in online burst events detection and has higher accuracy compared with other approaches.

Keywords

Burst event, abnormal message, microblog, message stream

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing | Social Media

Publication

Computers, Materials and Continua

Volume

60

Issue

1

First Page

213

Last Page

225

ISSN

1546-2218

Identifier

10.32604/cmc.2019.05601

Publisher

Tech Science Press

Embargo Period

2-12-2025

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Additional URL

https://doi.org/10.32604/cmc.2019.05601

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