Nowcasting of earthquake consequences using big social data

Messages posted to social media in the aftermath of a natural disaster are not only useful for detecting the event itself. More importantly, mining such deliberately dropped digital traces allows a precise situational awareness, from which the disaster's intensity - that is, the consequences on population and infrastructures - can be timely estimated. Yet, to date, the automatic assessment of damage has received little attention. Here, the authors explore feeding predictive models by tweets conveying on-the-ground social sensors observations to nowcast the perceived intensity of earthquakes.