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Using Crowd Sourced Content to Help Manage Emergency Events

  • Robert Power
  • Bella Robinson
  • Catherine Wise
Chapter

Abstract

The Emergency Situation Awareness (ESA) tool provides crowd-sourced information in near-real-time from Twitter about all-hazard events for emergency managers. ESA currently collects tweets from Australia and New Zealand and processes them to identify unexpected incidents, to monitor ongoing emergency events and provides access to an archive to explore past events. It is operated using a map based interactive web site and has processed over 2 billion tweets since September 2011. ESA has been developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and has been trialed by numerous emergency services organisations throughout Australia. Tweets are processed as a data stream using text mining techniques and natural language processing tools to identify content relevant to emergency managers. ESA is deployed as a distributed information architecture consisting of a combination of commodity open source technologies, such as an Apache Solr index, a relational database, messaging infrastructure, web servers and supporting software toolkits, as well as purpose built components for message burst detection, event identification and notification, message classification and clustering, geo-coding and searching. In this chapter, an overview of ESA is presented showing how tweets are gathered and processed. Three case studies are outlined explaining how ESA is used to detect earthquakes, monitor bushfire events and as a general all-hazard monitoring tool in a crisis coordination centre. We also note some of the issues we have encountered from using our tool and present an overview of our research road map noting the planned extensions and new features.

Keywords

Disaster Management Situation Awareness Situation Reporting System Architectures Social Media Twitter 

Notes

Acknowledgements

There have been many CSIRO staff involved in the ESA project. The authors thanks the contributions of colleagues Mark Cameron, John Colton, Sarvnaz Karimi, Andrew Lampert, John Lingad, Peter Marendy, David Ratcliffe, Saguna, Brooke Smith, Gavin Walker, Allan Yin, Jie Yin and Emily Zhou. There has also been further CSIRO support of ESA from senior management and business development: thanks to Sarah Dods, Alan Dormer, Simon Dunstall, Dimitrios Georgakopoulos, Iftah Gideoni, Charlie Hawkins, Ron Jones, Michael Kearney, Ian Oppermann and Cecile Paris.

There have been numerous collaborators from agencies supporting this work, especially Anthony Clarke (New South Wales Rural Fire Service), Jim Dance and Andrew Grace (Attorney-General’s Department), Daniel Jaksa (Geoscience Australia) and Adam Moss (Queensland Department of Community Safety).

Special note should be made to Bella Robinson who has been the main developer and architect of the ESA tool; Mark Cameron who originally came up with the concept for the tool, devised the alerting algorithm and has been responsible for gathering most of the user requirements; and John Colton who has provided oversight for the project and been the main contact point for user agencies.

The ESA project was originally financially supported by the Australian Government through the National Security Science and Technology Branch within the Department of the Prime Minister and Cabinet.

References

  1. 1.
    UN OCHA. (2014). World humanitarian data and trends. http://www.unocha.org/data-and-trends-2014/. Accessed January 21, 2015.
  2. 2.
    Stephenson, C., Handmer, J., & Haywood, A. (2012). Estimating the net cost of the 2009 black saturday bushfires to the affected regions. Technical Report, RMIT, Bushfire CRC, Victorian DSE, February 2012.Google Scholar
  3. 3.
    Hughes, A. L., Peterson, S., & Palen, L. (2015). Social media in emergency management. In Issues in disaster science and management: A critical dialogue between scientists and emergency managers. FEMA in Higher Education Program.Google Scholar
  4. 4.
    Olteanu, A., Vieweg, S., Castillo, C, (2015). What to expect when the unexpected happens: Social media communications across crises. In Computer Supported Cooperative Work, CSWC 2015, Vancouver, BC, Canada, March.Google Scholar
  5. 5.
    Thelwall, M., & Stuart, D. (2007). RUOK? Blogging communication technologies during crises. Journal Computer-Mediated Communication, 12(2), 523–548.CrossRefGoogle Scholar
  6. 6.
    Abel, F., Hauff, C., Houben, G.-J., Stronkman, R., & Tao, K. (2012). Twitcident: Fighting fire with information from social web streams. In Proceedings of the 21st International Conference Companion on World Wide Web, WWW ’12 Companion (pp. 305–308). Lyon, France: ACM.Google Scholar
  7. 7.
    Avvenuti, M., Cresci, S., Marchetti, A., Meletti, C., & Tesconi, M. (2014). EARS (Earthquake alert and report system): A real time decision support system for earthquake crisis management. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’14 (pp. 1749–1758). New York, USA: ACM.Google Scholar
  8. 8.
    Robinson, B., Power, R., & Cameron, M. (2013). An evidence based earthquake detector using Twitter. In Proceedings of the Workshop on Language Processing and Crisis Information (LPCI) 2013 (pp 1–9). October 14, 2013, Nagoya, Japan.Google Scholar
  9. 9.
    Power, R., Robinson, B., Colton, J., Cameron, M. (2014). Emergency situation awareness: Twitter case studies. In Proceedings of the 1st International Conference, ISCRAM-med, volume 196 of LNBIP (pp. 218–231). Toulouse, France, October. Springer International Publishing.Google Scholar
  10. 10.
    Sakaki, T., Okazaki, M., & Matsuo, Y. (2013). Tweet analysis for real-time event detection and earthquake reporting system development. IEEE Transactions on Knowledge and Data Engineering, 25(4), 919–931.CrossRefGoogle Scholar
  11. 11.
    American Red Cross. (2012). More Americans using mobile apps in emergencies. http://www.redcross.org/news/pressrelease/More-Americans-Using-Mobile-Apps-in-Emergencies. Accessed September 2, 2014.
  12. 12.
    Bruns, A., Burgess, J., Crawford, K., & Shaw, F. (2012, January). #qldfloods and @QPSMedia: Crisis communication on Twitter in the 2011 South East Queensland Floods.Google Scholar
  13. 13.
    Lindsay, B. (2011, September). Social media and disasters: Current uses, future options, and policy considerations. Congressional Research Service Report to Congress.Google Scholar
  14. 14.
    Verma, S., Vieweg, S., Corvey, W., Palen, L., Martin, J., Palmer, M., Schram, A., Anderson, K. (2011). Natural language processing to the rescue? Extracting ‘situational awareness’ tweets during mass emergency In Fifth International AAAI Conference on Weblogs and Social Media (ICWSM) (pp. 49–57). July 2011. Barcelona, Spain.Google Scholar
  15. 15.
    Yin, J., Lampert, A., Cameron, M., Robinson, B., & Power, R. (2012). Using social media to enhance emergency situation awareness. IEEE Intelligent Systems, 27(6), 52–59.Google Scholar
  16. 16.
    Power, R., Robinson, B., Ratcliffe, D. (2013). Finding fires with Twitter. In Proceedings of the Australasian Language Technology Association Workshop 2013 (ALTA 2013) (pp 80–89), December 2013. Brisbane, Australia.Google Scholar
  17. 17.
    Power, R., Robinson, B., Wise, C. (2013). Comparing web feeds and tweets for emergency management. Social Web for Disaster Management (SWDM) Workshop 2013 (pp. 1007–1010). WWW 2013 Companion, May 13–17, 2013, Rio de Janeiro, Brazil.Google Scholar
  18. 18.
    Power, R., Robinson, B., Wise, C., Cameron, M. (2013). Information integration for emergency management: Recent CSIRO case studies. In J. Piantadosi., R. S. Anderssen., & J. Boland (Eds.), MODSIM2013, 20th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (pp. 2061–2067). December 2013. ISBN: 978-0-9872143-3-1.Google Scholar
  19. 19.
    Cameron, M., Power, R., Robinson, B., & Yin, J. (2012). Emergency situation awareness from Twitter for crisis management. In Social Web for Disaster Management (SWDM) Workshop 2012. WWW 2012 Companion (pp. 695–698). April 16–20, 2012, Lyon, France. ACM 978-1-4503-1230-1/12/04.Google Scholar
  20. 20.
    Porter, M. F. (1980). An algorithm for suffix stripping. Program, 14(3), 130–137.CrossRefGoogle Scholar
  21. 21.
    Earle, P., Bowden, D., & Guy, M. (2012). Twitter earthquake detection: earthquake monitoring in a social world. Annals of GeoPhysics, 54(6), 708–715.Google Scholar
  22. 22.
    Power, R., Robinson, B., Colton, J., & Cameron, M. (2015). A case study for monitoring fires with Twitter. In Proceedings of the 12th International Conference on Information Systems for Crisis Response and Management (ISCRAM). Kristiansand, Norway, 24–27 May 2015. Springer International Publishing.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.CSIRO Data61CanberraAustralia

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