Identifying post-Disaster resource needs and availabilities from microblogs

Abstract

Microblogging sites like Twitter are increasingly being used for aiding post-disaster relief operations. In such situations, identifying needs and availabilities of various types of resources is critical for effective coordination of the relief operations. We focus on the problem of automatically identifying tweets that inform about needs and availabilities of resources, termed as need-tweets and availability-tweets respectively. Traditionally, pattern matching techniques are adopted to identify such tweets. In this work, we present novel retrieval methodologies, based on word embeddings, for automatically identifying need-tweets and availability-tweets. Experiments over tweets posted during two recent disaster events show that the proposed methodologies outperform prior pattern-matching techniques. © 2017 Association for Computing Machinery.