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The huge amount of information shared in Twitter during disaster events areutilized by government agencies and humanitarian organizations to ensure quickcrisis response and provide situational updates. However, the huge number oftweets posted makes manual identification of the relevant tweets impossible. Toaddress the information overload, there is a need to automatically generatesummary of all the tweets which can highlight the important aspects of thedisaster. In this paper, we propose an entropy and diversity based summarizer,termed as EnDSUM, specifically for disaster tweet summarization. Ourcomprehensive analysis on 6 datasets indicates the effectiveness of EnDSUM andadditionally, highlights the scope of improvement of EnDSUM.

EnDSUM: Entropy and Diversity based Disaster Tweet Summarization