Assessing disaster impacts and response using social media data in China: A case study of 2016 Wuhan rainstorm

Social media, with its ability to record human activities, has gained increasing attention from various fields. In this study, we developed a framework to assess disaster impacts with social media data, and examined the potential of information extraction with social media messages from Weibo platform to inform disaster response and recovery in China, using the case of 2016 Wuhan rainstorm and flood disaster. Temporal evolution of social media activities was investigated to track the process of the disaster, and further compared with observed precipitation data. Moreover, major impacts of the disaster were assessed through word frequency analysis of impact-related topics. Finally, place-related information were extracted to map the hotspots of the disaster. The results indicate that temporal variation of social media activities was consistent with the rainstorm process and significant positive correlation was found between social media activities and precipitation intensity. Word frequency analysis of impact-related topics revealed that transportation and daily life were most affected, meanwhile impacts on people's emotion and psychological activities were also notable. For hot spots affected by the disaster, more flooded sites were found in central urban districts, which are generally residential/industrial area or roads and other traffic-related places. This study demonstrated the utility of social media for disaster assessment, however ensuring the accuracy of online information and expanding the application for all phases of disaster management still pose substantial challenges for future research.