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    Li, Hongmin Caragea, Doina Caragea, Cornelia and Herndon, Nic 2018. Disaster response aided by tweet classification with a domain adaptation approach. Journal of Contingencies and Crisis Management, Vol. 26, Issue. 1, p. 16.

    Sarmiento, Hernan Poblete, Barbara and Campos, Jaime 2018. Domain-Independent Detection of Emergency Situations Based on Social Activity Related to Geolocations. p. 245.

    Reuter, Christian Hughes, Amanda Lee and Kaufhold, Marc-André 2018. Social Media in Crisis Management: An Evaluation and Analysis of Crisis Informatics Research. International Journal of Human–Computer Interaction, Vol. 34, Issue. 4, p. 280.

    Zubiaga, Arkaitz Aker, Ahmet Bontcheva, Kalina Liakata, Maria and Procter, Rob 2018. Detection and Resolution of Rumours in Social Media. ACM Computing Surveys, Vol. 51, Issue. 2, p. 1.

    Palen, Leysia and Hughes, Amanda L. 2018. Handbook of Disaster Research. p. 497.

    Meladianos, Polykarpos Xypolopoulos, Christos Nikolentzos, Giannis and Vazirgiannis, Michalis 2018. Advances in Information Retrieval. Vol. 10772, Issue. , p. 481.

    Imran, Muhammad Castillo, Carlos Diaz, Fernando and Vieweg, Sarah 2018. Processing Social Media Messages in Mass Emergency. p. 507.

    Akerkar, Rajendra 2018. Smart Technologies for Emergency Response and Disaster Management. p. 144.

    Bacigalupe, Gonzalo and Velasco-Martin, Javier 2018. Complex Networks IX. p. 283.

    Chernobrov, Dmitry 2018. Digital Volunteer Networks and Humanitarian Crisis Reporting. Digital Journalism, p. 1.

    Reuter, Christian and Kaufhold, Marc-André 2018. Fifteen years of social media in emergencies: A retrospective review and future directions for crisis Informatics. Journal of Contingencies and Crisis Management, Vol. 26, Issue. 1, p. 41.

    Lazreg, Mehdi Ben Goodwin, Morten and Granmo, Ole-Christoffer 2017. Vector representation of non-standard spellings using dynamic time warping and a denoising autoencoder. p. 1444.

    Tarasconi, Francesco Farina, Michela Mazzei, Antonio and Bosca, Alessio 2017. The role of unstructured data in real-time disaster-related social media monitoring. p. 3769.

    Nugent, Tim Petroni, Fabio Raman, Natraj Carstens, Lucas and Leidner, Jochen L. 2017. A comparison of classification models for natural disaster and critical event detection from news. p. 3750.

    Acerbo, Flavia Sofia and Rossi, Claudio 2017. Filtering informative tweets during emergencies. p. 1.

    Shibuya, Yuya 2017. Mining social media for disaster management: Leveraging social media data for community recovery. p. 3111.

    Vedula, Nikhita Parthasarathy, Srinivasan and Shalin, Valerie L. 2017. Predicting Trust Relations Within a Social Network. p. 53.

    Nazer, Tahora H. Xue, Guoliang Ji, Yusheng and Liu, Huan 2017. Intelligent Disaster Response via Social Media Analysis A Survey. ACM SIGKDD Explorations Newsletter, Vol. 19, Issue. 1, p. 46.

    Morstatter, Fred 2016. Using Biased Social Samples for Disaster Response: Extended Abstract. p. 456.

    Palen, Leysia and Anderson, Kenneth M. 2016. Crisis informatics—New data for extraordinary times. Science, Vol. 353, Issue. 6296, p. 224.

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    Big Crisis Data
    • Online ISBN: 9781316476840
    • Book DOI: https://doi.org/10.1017/CBO9781316476840
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Book description

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.

Reviews

‘Castillo has provided an accessible path through a wide and sometimes unwieldy literature on crisis informatics. This book has an important and timely focus on big data issues, which both challenge and enlighten our understanding of human behavior in disaster events.’

Leysia Palen - Professor of Computer Science, and Professor and Founding Chair of the Department of Information Science, University of Colorado, Boulder

‘Gaining situational awareness in a disaster is critical and time sensitive in nature. Social media presents the possibilities of a new and exciting data source to help improve response in the early hours and days of a crisis. Castillo has not only researched, but also contributed to building technologies that help both to make sense of social media and to integrate it into existing information flows and decision-making processes. This book helps walk the reader through the state of the art in several aspects of the big crisis data field, including many elements that are important for these technologies to have real-world impact.'

Andrej Verity - Co-Founder, Digital Humanitarian Network, and Information Management Officer, United Nations Office for the Coordination of Humanitarian Affairs

‘Social media has played an indispensable role during all of the recent disasters and crises. If you are a researcher looking for ways to make sense of the data that inundates us during such events or a practitioner struggling to make such data actionable, this book needs to be your first source. Castillo has masterfully synthesized a large number of techniques and capabilities in a unified framework to cover this already broad field for the reader.'

Amit Sheth - Executive Director of Kno.e.sis, Wright State University, Ohio

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