Finding Eyewitness Tweets During Crises

Abstract

Disaster response agencies incorporate social media as a source of fast-breaking information to understand the needs of people affected by the many crises that occur around the world. These agencies look for tweets from within the region affected by the crisis to get the latest updates on the status of the affected region. However only 1% of all tweets are “geotagged” with explicit location information. In this work we seek to identify non-geotagged tweets that originate from within the crisis region. Towards this, we address three questions: (1) is there a difference between the language of tweets originating within a crisis region, (2) what linguistic patterns differentiate within-region and outside-region tweets, and (3) can we automatically identify those originating within the crisis region in real-time?.