Big Crisis Data
Social Media in Disasters and Time-Critical Situations
Book by Carlos Castillo. Cambridge University Press, 2016.
Social media is an invaluable source of time-critical information during a crisis. However, emergency response and humanitarian relief organizations that would like to use this information struggle with an avalanche of social media messages that exceeds human capacity to process. Emergency managers, decision makers, and affected communities can make sense of social media through a combination of machine computation and human compassion — expressed by thousands of digital volunteers who publish, process, and summarize potentially life-saving information.
This book brings together computational methods from many disciplines: natural language processing, semantic technologies, data mining, machine learning, network analysis, human-computer interaction, and information visualization, focusing on methods that are commonly used for processing social media messages under time-critical constraints, and offering more than 500 references to in-depth information.
The first part (Chapters 2-6) focuses on the technical aspects of data processing, and follows computing disciplines of databases, natural language processing, machine learning, network analysis, and online algorithms.
The second part (Chapters 8-11) focuses on the context in which data processing occurs, and is more oriented to studies of information sciences and human factors, including crowdsourcing, human-computer interaction, computer-supported collaborative work, and information visualization.
Table of contents and preface (116 KB).
For pointers to data and tools, see the book's wiki page at the Humanitarian Computing Library, including: