Big data analytics for disaster response and recovery through sentiment analysis

作者：

Highlights：

• Social networks are increasingly used for emergency communications and help related requests during the disaster.

• A methodology is proposed to visualize and analyze the sentiments on the various basic needs of the people affected by the disaster.

• The combination of subjective phrase and machine learning algorithm yields better classification accuracy for disaster data.

• Real-time categorization and classification of social media big data ensures effective disaster response and recovery.

摘要

•Social networks are increasingly used for emergency communications and help related requests during the disaster.•A methodology is proposed to visualize and analyze the sentiments on the various basic needs of the people affected by the disaster.•The combination of subjective phrase and machine learning algorithm yields better classification accuracy for disaster data.•Real-time categorization and classification of social media big data ensures effective disaster response and recovery.

论文关键词：Big data,Disaster management,Natural language processing,Sentiment analysis,Text classification,Social media analysis

论文评审过程：Received 22 September 2017, Revised 17 May 2018, Accepted 17 May 2018, Available online 23 May 2018, Version of Record 23 May 2018.

论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2018.05.004