Improving Disaster Response by Combining Automated Text Information Extraction from Images and Text on Social Media.

During disasters, social media can serve as a valuable source of real-time information about the impacts on people and infrastructure. However, due to the lack of geographical information in most social media posts, this information is often underutilized by first responders. Previous research has attempted to estimate the location of individual social media posts using text and image analysis, but limitations still exist in fine-grained disaster area mapping. To address this issue, this paper analyses the performance of combining text from social media post with textual information from the images on improving the geolocation of social media information during a disaster.