  Social Media websites have disseminated digital devices to the public, making
information sharing easier and faster. Exchanging textual data is the most
popular communication among social media users. It has become a necessity for
treatment. Event extraction on the other hand indicates an understanding of
events across social media posts streams. Event extraction helps to take faster
corrective action in natural disasters, and may save lives. The main objective
of the task is to develop specific model to detect and extract the events
(incidents) identified in the digital text. We proposed here a model based on
deep recurrent networks to extract the events from social media feeds.
