Tweet trend analysis in an emergency situation
Proceedings of the Special Workshop on Internet and Disasters
Twitter in disaster mode: opportunistic communication and distribution of sensor data in emergencies
Proceedings of the 3rd Extreme Conference on Communication: The Amazon Expedition
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In recent disaster events, social media has proven to be an effective communication tool for affected people. The corpus of generated messages contains valuable information about the situation, needs, and locations of victims. We propose an approach to extract significant aspects of user discussions to better inform responders and enable an appropriate response. The methodology combines location based division of users together with standard text mining (term frequency inverse document frequency) to identify important topics of conversation in a dynamic geographic network. We further suggest that both topics and movement patterns change during a disaster, which requires identification of new trends. When applied to an area that has suffered a disaster, this approach can provide 'sensemaking' through insights into where people are located, where they are going and what they communicate when moving.