BITS_PILANI@IMRiDis-FIRE 2017: Information Retrieval from Microblog during Disasters

Abstract

Microblogging sites like Twitter are increasingly being used for aiding relief operations during disaster events. In such situations, identifying actionable information like needs and availabilities of various types of resources is critical for effective coordination of post disaster relief operations. However, such critical information is usually submerged within a lot of conversational content, such as sympathy for the victims of the disaster. Hence, automated IR techniques are needed to find and process such information. In this paper, we utilize word vector embeddings along with fastText sentence classification algorithm to perform the task of classification of tweets posted during natural disasters.