The use of microblogging platforms such as Twitter during crises has become
widespread. More importantly, information disseminated by affected people
contains useful information like reports of missing and found people, requests
for urgent needs etc...
For rapid crisis response, humanitarian organizations
look for situational awareness information to understand and assess the
severity of the crisis. In this paper, we present a novel framework (i) to
generate abstractive summaries useful for situational awareness, and (ii) to
capture sub-topics and present a short informative summary for each of these
topics. A summary is generated using a two stage framework that first extracts
a set of important tweets from the whole set of information through an
Integer-linear programming (ILP) based optimization technique and then follows
a word graph and concept event based abstractive summarization technique to
produce the final summary. High accuracies obtained for all the tasks show the
effectiveness of the proposed framework.