Combining automatic and manual approaches: Towards a framework for discovering themes in disaster-related tweets

• Main Authors: Syliongka, Leif Romeritch, Oco, Nathaniel, Lam, Alron Jan, Soriano, Cheryll Ruth, Roldan, Ma. Divina Gracia, Magno, Francisco, Cheng, Charibeth
• Format: text
• Published: Animo Repository 2015
• Subjects: cNatural language processing (Computer science); Document clustering; Typhoon Haiyan, 2013; Microblogs; Computer Sciences; Emergency and Disaster Management; Models and Methods
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/2745
• Institution: De La Salle University

In this paper, we present a framework that combines automatic and manual approaches to discover themes in disaster-related tweets. As case study, we decided to focus on tweets related to typhoon Haiyan, which caused billions of dollars in damages. We collected tweets from November 2013 to March 2014...