Analyzing spatial data from Twitter during a disaster

被引：0
|
作者：
Venturini, Luca [1 ]
Di Corso, Evelina [1 ]
机构：
[1] Politecn Torino, Dipartimento Automat & Informat, Turin, Italy
来源：
2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2017年
关键词：
spatial data analysis; Twitter; disasters and mass emergencies;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Social media can be an invaluable help in a mass emergency, but the information handling can be challenging. One major concern is identifying posts related to the area, or pinning them on a map. This exploratory study analyzes the spatial data coming with tweets during two natural disasters, an earthquake and a hurricane. Geo-tagged tweets confirm to be a small fraction of all tweets and disasters within a limited region appear to be a niche topic in the whole stream. The results can help researchers and practitioners in the design of tools to identify these messages.
引用
收藏
页码：3779 / 3783
页数：5
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