  Social media has quickly grown into an essential tool for people to
communicate and express their needs during crisis events. Prior work in
analyzing social media data for crisis management has focused primarily on
automatically identifying actionable (or, informative) crisis-related messages.
In this work, we show that recent advances in Deep Learning and Natural
Language Processing outperform prior approaches for the task of classifying
informativeness and encourage the field to adopt them for their research or
even deployment. We also extend these methods to two sub-tasks of
informativeness and find that the Deep Learning methods are effective here as
well.
