  During a disaster event, two types of information that are especially useful
for coordinating relief operations are needs and availabilities of resources
(e.g., food, water, medicines) in the affected region. Information posted on
microblogging sites is increasingly being used for assisting post-disaster
relief operations. In this context, two practical challenges are (i)~to
identify tweets that inform about resource needs and availabilities (termed as
need-tweets and availability-tweets respectively), and (ii)~to automatically
match needs with appropriate availabilities. While several works have addressed
the first problem, there has been little work on automatically matching needs
with availabilities. The few prior works that attempted matching only
considered the resources, and no attempt has been made to understand other
aspects of needs/availabilities that are essential for matching in practice. In
this work, we develop a methodology for understanding five important aspects of
need-tweets and availability-tweets, including what resource and what quantity
is needed/available, the geographical location of the need/availability, and
who needs / is providing the resource. Understanding these aspects helps us to
address the need-availability matching problem considering not only the
resources, but also other factors such as the geographical proximity between
the need and the availability. To our knowledge, this study is the first
attempt to develop methods for understanding the semantics of need-tweets and
availability-tweets. We also develop a novel methodology for matching
need-tweets with availability-tweets, considering both resource similarity and
geographical proximity. Experiments on two datasets corresponding to two
disaster events, demonstrate that our proposed methods perform substantially
better matching than those in prior works.
