<![CDATA[For timely and efficient reactions to disasters, collecting vital and right information is essential. In recent decades, social media platforms such as Twitter, Facebook, Linkedin, Instagram have become valuable sources of information in disaster times. However, the reliability, volume, and velocity of information remain a major concern; this is particular about information issued from disaster locations. This paper proposes an approach for tracking the location of people in danger during times of disaster. The procedure is based on the Twitter application programming interface (API) by using natural language processing (NLP) and big data tools. A number of tweets were analyzed and an accuracy of 86.11% was actualized.]]>
