Citation

Ma T, Zhao YW, Zhou H, Tian Y, Al-Dhelaan A, Al-Rodhaan M. Expert Syst. Appl. 2019; 115: 346-355.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.eswa.2018.08.010

PMID

unavailable

Abstract

In this paper, we will propose a novel approach based on graph analysis which will use community structure detection algorithm to detect topics in the keywords graph of micro-blogging data. Furthermore, considering the specificity of the Sina microblogging, we propose novel keywords filtering model and graph generation algorithm to meet the dual requirements of topic detection and community detection. We validate our approach on a big natural disaster dataset from Sina micro-blog, in which about 103 micro-blogging posts with about 104 distinct feature tags. The experimental results definitely revealed the relationship between the keywords and the natural disaster topics. Our methodology is a scalable method which can adapt to the changes in the amount of data. Especially, we can get abundant information about natural disasters in the topic detection and help the government guide the rescue of disasters.

Language: en

Keywords

Community detection; Graph analysis; Natural disaster; Sina microblogging; Topic detection