A survey on event and subevent detection from microblog data towards crisis management

AI and data science for smart emergency, crisis and disaster resilience

“…The applications of the above methods can be seen in various ECD problems, objectives, and developments over the lifespan of ECD [ 20 – 22 ]. Examples of AISDR applications include: Unsupervised learning applied to assess and detect damages, damage areas or damage severity; event or subevent detection [ 23 ] in disaster. Supervised learning applied to categorize, identify, reidentify, or recognize damage types and severity; estimate disaster relief population based on crowdsourcing, web mapping and social media data; score rescue priority for immediate or low-priority aid, search or rescue of affected population; allocate demand resources, or match rescue teams with affected people by involving medical features and classify severity.…”

“…Unsupervised learning applied to assess and detect damages, damage areas or damage severity; event or subevent detection [ 23 ] in disaster.…”