  Social media posts contain an abundant amount of information about public
opinion on major events, especially natural disasters such as hurricanes. Posts
related to an event, are usually published by the users who live near the place
of the event at the time of the event. Special correlation between the social
media data and the events can be obtained using data mining approaches. This
paper presents research work to find the mappings between social media data and
the severity level of a disaster. Specifically, we have investigated the
Twitter data posted during hurricanes Harvey and Irma, and attempted to find
the correlation between the Twitter data of a specific area and the hurricane
level in that area. Our experimental results indicate a positive correlation
between them. We also present a method to predict the hurricane category for a
specific area using relevant Twitter data.
