Abstract
Social media data have emerged as a new source for detecting and monitoring disaster events. A number of recent studies have suggested that social media data streams can be used to mine actionable data for emergency response and relief operation. However, no effort has been made to classify social media data into stages of disaster management (mitigation, preparedness, emergency response, and recovery), which has been used as a common reference for disaster researchers and emergency managers for decades to organize information and streamline priorities and activities during the course of a disaster. This paper makes an initial effort in coding social media messages into different themes within different disaster phases during a time-critical crisis by manually examining more than 10,000 tweets generated during a natural disaster and referencing the findings from the relevant literature and official government procedures involving different disaster stages. Moreover, a classifier based on logistic regression is trained and used for automatically mining and classifying the social media messages into various topic categories during various disaster phases. The classification results are necessary and useful for emergency managers to identify the transition between phases of disaster management, the timing of which is usually unknown and varies across disaster events, so that they can take action quickly and efficiently in the impacted communities. Information generated from the classification can also be used by the social science research communities to study various aspects of preparedness, response, impact and recovery.
Highlights
For several decades, disaster researchers and emergency managers have typically relied on a four-phase categorization to understand and manage disasters [1]
It has been acknowledged that public source data can help in all phases of disaster management [4], and social media mining for disaster response and coordination has been receiving an increasing level of attention from the research community
The goal of this article is to investigate the nature of tweet content generated within the time span of a disaster, and define a list of content categories taking into consideration the information involved in disaster phases including preparedness, emergency response, and recovery
Summary
Disaster researchers and emergency managers have typically relied on a four-phase categorization (mitigation, preparedness, response, and recovery) to understand and manage disasters [1]. The categorization provides a common framework for the researchers to organize, compare, and share research findings. It serves as a time reference for practitioners to predict challenges and damage, prioritize functions, and streamline activities during the course of disaster management [2,3]. Using social media data has several advantages over traditional means of data collection to understand multiple phases of disaster management. Methodologies, such as phone calls, direct observations, or personal interviews, were commonly practiced by disaster responders and damage evaluators to gain situational awareness and investigate impacted populations. Even with the research at rudimentary level, social media data has presented interesting snapshots about human society at a macro scale with agility that could only be dreamed of by traditional surveys [13]
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