气候变化领域集成服务门户(CCPortal): SEPM: rapid seism emergency information processing based on social media

CCPortal

DOI	10.1007/s11069-020-04185-4
	SEPM: rapid seism emergency information processing based on social media
	Bai X.; Liu X.; Lu S.; Zhang X.; Su W.; Su X.; Li L.
发表日期	2020
ISSN	0921030X
起始页码	659
结束页码	679
卷号	104 期号:1
英文摘要	With the development of network communication technology and the popularity of social media tools, earthquake-related information has been easily published and disseminated in social networks. This study focuses on obtaining this information and providing guidance for earthquake emergency work. A processing model is proposed to obtain earthquake information from social networks. First, a configuration-driven data acquisition module is designed to acquire earthquake information. Second, according to the characteristics of earthquake information in social media, a seismic emergency thesaurus is selected, and weight is calculated. To solve the low accuracy of inter-class classification, an improved mutual term frequency–inverse document frequency (MTF–IDF) algorithm is proposed. Finally, the thesaurus database is used to classify the acquired earthquake information. By taking the Lushan and Jiuzhaigou earthquakes as examples, the improved MTF–IDF algorithm shows a better effect on the selection of seismic keywords than the traditional TF–IDF algorithm; the F1-measure in classification has increased from 79.86 to 86.93%. The proposed model can rapidly and easily acquire and classify earthquake information according to different sources, which can provide timely information and support for disaster relief. © 2020, Springer Nature B.V.
关键词	Earthquake emergency information Information classification Social media TF–IDF Thesaurus weight calculation
英文关键词	classification; disaster relief; earthquake event; information processing; social media; social network
语种	英语
来源期刊	Natural Hazards
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/205592
作者单位	College of Information and Electrical Engineering, China Agricultural University, Beijing, 100083, China; University of Michigan, Lansing, 43210, United States; College of Information, Beijing Forestry University, Beijing, 100083, China
推荐引用方式 GB/T 7714	Bai X.,Liu X.,Lu S.,et al. SEPM: rapid seism emergency information processing based on social media[J],2020,104(1).
APA	Bai X..,Liu X..,Lu S..,Zhang X..,Su W..,...&Li L..(2020).SEPM: rapid seism emergency information processing based on social media.Natural Hazards,104(1).
MLA	Bai X.,et al."SEPM: rapid seism emergency information processing based on social media".Natural Hazards 104.1(2020).