DOI: 10.1007/s11069-021-04528-9
论文题名: Social media information sharing for natural disaster response
作者: Dong Z.S. ; Meng L. ; Christenson L. ; Fulton L.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 107, 期: 3 起始页码: 2077
结束页码: 2104
语种: 英语
中文关键词: Big data analytics
; Disaster response
; Machine learning
; Sentiment analysis
; Social media
; Twitter
英文关键词: data set
; disaster management
; hazard management
; information management
; machine learning
; natural disaster
; social media
英文摘要: Social media has become an essential channel for posting disaster-related information, which provides governments and relief agencies real-time data for better disaster management. However, research in this field has not received sufficient attention, and extracting useful information is still challenging. This paper aims to improve disaster relief efficiency via mining and analyzing social media data like public attitudes toward disaster response and public demands for targeted relief supplies during different types of disasters. We focus on different natural disasters based on properties such as types, durations, and damages, which contains a total of 41,993 tweets. In this paper, public perception is assessed qualitatively by manually classified tweets, which contain information like the demand for targeted relief supplies, satisfactions of disaster response, and public fear. Public attitudes to natural disasters are studied via a quantitative analysis using eight machine learning models. To better provide decision-makers with the appropriate model, the comparison of machine learning models based on computational time and prediction accuracy is conducted. The change of public opinion during different natural disasters and the evolution of peoples’ behavior of using social media for disaster relief in the face of the identical type of natural disasters as Twitter continues to evolve are studied. The results in this paper demonstrate the feasibility and validation of the proposed research approach and provide relief agencies with insights into better disaster management. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168991
Appears in Collections: 气候变化与战略
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作者单位: Ingram School of Engineering, Texas State University, San Marcos, TX 78666, United States; School of Health Administration, Texas State University, San Marcos, TX 78666, United States
Recommended Citation:
Dong Z.S.,Meng L.,Christenson L.,et al. Social media information sharing for natural disaster response[J]. Natural Hazards,2021-01-01,107(3)