During times of disasters, users can act as powerful social sensors, because of the significant amount of data they generate on social media. Indeed, they contribute to creating situational awareness by informing what is happening in the affected community during the incident. In this context, this article focuses on the text-processing module in CASPER, a knowledge-based system that integrates event detection and sentiment tracking. The performance of the system was tested with the natural disaster of wildfires.
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