Enhancing Disaster Response with Automated Text Information Extraction from Social Media Images

This is the authors' abstract. We don't add key points for this paper.

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 explores the feasibility of automatically extracting textual information from social media images to enhance the creation of a disaster area map. This paper evaluates the effectiveness of the proposed approach and its potential impact on improving the geolocation of social media information during a disaster.