• Proliferation of micro blogging and the importance of on-topic tweets for time-critical situational awareness to disaster-affected communities and professional responders

• Challenges

o finding informative and relevant information to accelerate disaster response

o Information overload: Labor-intensive content moderation process as a bottleneck to quickly identify task-related information from incoming messages from the crowd

 Auto filtering of relative and informative messages

 Automatic categorization of messages

• Research Gap

o Several machine learning techniques have been applied in this domain but all features considered in the classifiers are selected in a data-driven approach without a sound understanding of decision-makers’ information needs and requirements, may result in ineffective filtering and misclassification.

o By incorporating the key words generated by a top-down approach with structured domain-knowledge proposed, the accuracy of classification still has the potentials for improvement

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