Big Crisis Data: Social Media in Disasters and Time-Critical Situations

by Carlos Castillo

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 the 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.

224 pages, Hardcover

Published July 4, 2016

Reviews

[Cristián S · Rating 3 out of 5]

This book is an introduction to the crisis data management, handling and volunteering opportunities from the computer science point of view. I read it thinking it was going to be more about success/failure stories, with highlighted insights. Instead, it is more like an academic survey, with references to other works that expand over each subject. The references are good, although it is a little outdated, as it is a rapidly changing subject, and the COVID-19 pandemic changed many online aid organizations. I am from the machine learning community and participate actively in some online volunteering communities, and I thought I was going to get new point of views of the subject, but I feel that I didn't learn much from this book.