A behavior analytics approach to identifying tweets from crisis regions

The growing popularity of Twitter as an information medium has allowed unprecedented access to first-hand information during crises and mass emergency situations. Due to the sheer volume of information generated during a disaster, a key challenge is to filter tweets from the crisis region so their analysis can be prioritized. In this paper, we introduce the task of identifying whether a tweet is generated from crisis regions and formulate it as a decision problem. This problem is challenging due to the fact that only ∼1% of all tweets have location information. Existing approaches tackle this problem by predicting the location of the user using historical tweets from users or their social network. As collecting historical information is not practical during emergency situations, we investigate whether it is possible to determine that a tweet originates from the crisis region through the information in the tweet and the publishing user's profile.