Summarizing Microblogs for Emergency Relief and Preparedness

Abstract In recent years, Online Social Media (OSM) has established itself as one of the most significant sources of situational information during any natural or man-made disaster. Real-time summarization of this rapidly posted huge volume of crowdsourced responses is a common requirement for emergency relief and preparedness when time is critical. Our semi-automatic method exploits a combination of SumBasic Summarizer and different classifiers to summarize the topic wise relevant microblogs (tweets) extracted through manually identified query term matching. The result of our participation in the SMERP 2017 Data Challenge Track shows that it is an effective approach in summarizing tweets in a disaster scenario and can be replicated across diverse domains.

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