IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v20y2018i5d10.1007_s10796-018-9833-z.html
   My bibliography  Save this article

CrisMap: a Big Data Crisis Mapping System Based on Damage Detection and Geoparsing

Author

Listed:
  • Marco Avvenuti

    (University of Pisa)

  • Stefano Cresci

    (National Research Council (CNR))

  • Fabio Del Vigna

    (National Research Council (CNR))

  • Tiziano Fagni

    (National Research Council (CNR))

  • Maurizio Tesconi

    (National Research Council (CNR))

Abstract

Natural disasters, as well as human-made disasters, can have a deep impact on wide geographic areas, and emergency responders can benefit from the early estimation of emergency consequences. This work presents CrisMap, a Big Data crisis mapping system capable of quickly collecting and analyzing social media data. CrisMap extracts potential crisis-related actionable information from tweets by adopting a classification technique based on word embeddings and by exploiting a combination of readily-available semantic annotators to geoparse tweets. The enriched tweets are then visualized in customizable, Web-based dashboards, also leveraging ad-hoc quantitative visualizations like choropleth maps. The maps produced by our system help to estimate the impact of the emergency in its early phases, to identify areas that have been severely struck, and to acquire a greater situational awareness. We extensively benchmark the performance of our system on two Italian natural disasters by validating our maps against authoritative data. Finally, we perform a qualitative case-study on a recent devastating earthquake occurred in Central Italy.

Suggested Citation

  • Marco Avvenuti & Stefano Cresci & Fabio Del Vigna & Tiziano Fagni & Maurizio Tesconi, 2018. "CrisMap: a Big Data Crisis Mapping System Based on Damage Detection and Geoparsing," Information Systems Frontiers, Springer, vol. 20(5), pages 993-1011, October.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:5:d:10.1007_s10796-018-9833-z
    DOI: 10.1007/s10796-018-9833-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-018-9833-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-018-9833-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stefan Stieglitz & Christian Meske & Björn Ross & Milad Mirbabaie, 2020. "Going Back in Time to Predict the Future - The Complex Role of the Data Collection Period in Social Media Analytics," Information Systems Frontiers, Springer, vol. 22(2), pages 395-409, April.
    2. Sajjad Ahadzadeh & Mohammad Reza Malek, 2021. "Earthquake Damage Assessment Based on User Generated Data in Social Networks," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    3. Pavel Petrov, 2023. "Practical approach for modifying existing geocoding system from equal angular to equal area," Economics and computer science, Publishing house "Knowledge and business" Varna, issue 2, pages 43-65.
    4. Rafael Prieto Curiel & Stefano Cresci & Cristina Ioana Muntean & Steven Richard Bishop, 2020. "Crime and its fear in social media," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-12, December.
    5. Jennifer Fromm & Kaan Eyilmez & Melina Baßfeld & Tim A. Majchrzak & Stefan Stieglitz, 2023. "Social Media Data in an Augmented Reality System for Situation Awareness Support in Emergency Control Rooms," Information Systems Frontiers, Springer, vol. 25(1), pages 303-326, February.
    6. Saptarshi Ghosh & Kripabandhu Ghosh & Debasis Ganguly & Tanmoy Chakraborty & Gareth J. F. Jones & Marie-Francine Moens & Muhammad Imran, 2018. "Exploitation of Social Media for Emergency Relief and Preparedness: Recent Research and Trends," Information Systems Frontiers, Springer, vol. 20(5), pages 901-907, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:20:y:2018:i:5:d:10.1007_s10796-018-9833-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.