Paper Info
Title
Area Definition and Public Opinion Research of Natural Disaster Based on Micro-blog Data.
Abstract
Natural disasters have long disturbed people’s normal lives. How to effectively identify and assess natural disaster-affected areas and further control network grievances is of great significance. This paper takes the floods in Hunan Province of China in 2017 as an example, based on the data sources of Sina Weibo, and combines text analysis and image analysis technology to define the disaster scope of natural disasters, and then uses sentimental analysis method and correlation analysis method to study the network public opinion in the disaster area. In this paper, the average accuracy and recall rate of the model which combines image analysis and text analysis to define the disaster area are 72.10% and 81.59% respectively, which effectively realizes the definition of flood disaster area in Hunan Province. In addition, this paper finds out the law of the development and change of network public opinion, and puts forward the opinions and suggestions on the determination of disaster area, the relief of disaster and the control of network public opinion.
Year
DOI
Venue
2019
10.1016/j.procs.2019.12.030
Procedia Computer Science
Keywords
Field
DocType
Natural Disasters,Text Analysis,Image Recognition,Classification,Sentiment Analysis,Public Opinion Management
Data science,Data mining,Social media,Recall rate,Computer science,Sentiment analysis,Microblogging,China,Natural disaster,Public opinion,Disaster area,Flood myth
Conference
Volume
ISSN
Citations 
162
1877-0509
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Yue He110516.62
Lijun Wen200.34
Tingting Zhu300.34