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    Analyzing Crowd-Sourced Information and Social Media for Crisis Management

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    Lefticaru_Book_Chapter.pdf (478.6Kb)
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    Publication date
    2017-03
    Author
    Andrews, S.
    Day, T.
    Domdouzis, K.
    Hirsch, L.
    Lefticaru, Raluca
    Orphanides, C.
    Keyword
    ATHENA
    SAS content categorization
    Formal concept analysis
    Social media
    Law enforcement agencies
    Rights
    © 2017 Springer. Reproduced in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-52419-1_6
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    The analysis of potentially large volumes of crowd-sourced and social media data is central to meeting the requirements of the ATHENA project. Here, we discuss the various stages of the pipeline process we have developed, including acquisition of the data, analysis, aggregation, filtering, and structuring. We highlight the challenges involved when working with unstructured, noisy data from sources such as Twitter, and describe the crisis taxonomies that have been developed to support the tasks and enable concept extraction. State-of-the-art techniques such as formal concept analysis and machine learning are used to create a range of capabilities including concept drill down, sentiment analysis, credibility assessment, and assignment of priority. We ground many of these techniques using results obtained from a set of tweets which emerged from the Colorado wildfires of 2012 in order to demonstrate the applicability of our work to real crisis scenarios.
    URI
    http://hdl.handle.net/10454/17662
    Version
    Accepted Manuscript
    Citation
    Andrews S, Day T, Domdouzis K et al (2017) Analyzing Crowd-Sourced Information and Social Media for Crisis Management. In: Akhgar B, Staniforth A and Waddington D (Eds) Application of Social Media in Crisis Management. Transactions on Computational Science and Computational Intelligence. New York: Springer International Publishing.
    Link to publisher’s version
    https://doi.org/10.1007/978-3-319-52419-1_6
    Type
    Book chapter
    Collections
    Engineering and Informatics Publications

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