F. Alam et al. A Twitter Tale of Three Hurricanes A Twitter Tale of Three Hurricanes: Harvey, Irma, and Maria Firoj Alam Ferda Ofli Qatar Computing Research Institute Qatar Computing Research Institute Hamad Bin Khalifa University Hamad Bin Khalifa University Doha, Qatar Doha, Qatar
[email protected] fofl
[email protected] Muhammad Imran Michael Aupetit Qatar Computing Research Institute Qatar Computing Research Institute Hamad Bin Khalifa University Hamad Bin Khalifa University Doha, Qatar Doha, Qatar
[email protected] [email protected] ABSTRACT People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools to analyze high-volume and high-velocity data streams. This work presents an extensive multidimensional analysis of textual and multimedia content from millions of tweets shared on Twitter during the three disaster events. Specifically, we employ various Artificial Intelligence techniques from Natural Language Processing and Computer Vision fields, which exploit different machine learning algorithms to process the data generated during the disaster events. Our study reveals the distributions of various types of useful information that can inform crisis managers and responders as well as facilitate the development of future automated systems for disaster management. Keywords social media, image processing, text classification, named-entity recognition, topic modeling, disaster management INTRODUCTION Three devastating natural disasters in 2017, namely Hurricane Harvey, Hurricane Irma, and Hurricane Maria, arXiv:1805.05144v2 [cs.SI] 15 May 2018 caused catastrophic damage worth billions of dollars and numerous fatalities, and left thousands of affected people.