Using AI and Social Media Multimodal Content for Disaster Response and Management: Opportunities, Challenges, and Future Directions. Issue 5 (September 2020)

• Record Type: Journal Article
• Authors: Imran, Muhammad; Ofli, Ferda; Caragea, Doina; Torralba, Antonio
• Is Part Of: Information processing & management. Volume 57:Issue 5(2020:Sep.)
• Publication Date: 2020-09
• Subjects: Social media -- Artificial intelligence -- Natural language processing -- Computer vision -- Multimodal learning; Information storage and retrieval systems -- Periodicals; Information science -- Periodicals; Systèmes d'information -- Périodiques; Sciences de l'information -- Périodiques; Information science; Information storage and retrieval systems; Periodicals; 658.4038
• DOI: 10.1016/j.ipm.2020.102261
• Languages: English
• ISSNs: 0306-4573

Abstract

Abstract: People increasingly use Social Media (SM) platforms such as Twitter and Facebook during disasters and emergencies to post situational updates including reports of injured or dead people, infrastructure damage, requests of urgent needs, and the like. Information on SM comes in many forms, such as textual messages, images, and videos. Several studies have shown the utility of SM information for disaster response and management, which encouraged humanitarian organizations to start incorporating SM data sources into their workflows. However, several challenges prevent these organizations from using SM data for response efforts. These challenges include near-real-time information processing, information overload, information extraction, summarization, and verification of both textual and visual content. We highlight various applications and opportunities of SM multimodal data, latest advancements, current challenges, and future directions for the crisis informatics and other related research fields.