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    Event classification and location prediction from tweets during disasters

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    Publication date
    2019-12
    Author
    Singh, J.P.
    Dwivedi, Y.K.
    Rana, Nripendra P.
    Kumar, A.
    Kapoor, K.K.
    Keyword
    Disaster management
    Geo-tagging
    Location inference
    Social media
    Twitter
    Rights
    (c) 2019 The Authors. This is an Open Access article distributed under the Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0)
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Social media is a platform to express one’s view in real time. This real time nature of social media makes it an attractive tool for disaster management, as both victims and officials can put their problems and solutions at the same place in real time. We investigate the Twitter post in a flood related disaster and propose an algorithm to identify victims asking for help. The developed system takes tweets as inputs and categorizes them into high or low priority tweets. User location of high priority tweets with no location information is predicted based on historical locations of the users using the Markov model. The system is working well, with its classification accuracy of 81%, and location prediction accuracy of 87%. The present system can be extended for use in other natural disaster situations, such as earthquake, tsunami, etc., as well as man-made disasters such as riots, terrorist attacks etc. The present system is first of its kind, aimed at helping victims during disasters based on their tweets.
    URI
    http://hdl.handle.net/10454/18072
    Version
    Published version
    Citation
    Singh JP, Dwivedi YK, Rana NP et al (2019) Event classification and location prediction from tweets during disasters. Annals of Operations Research. 283(1-2): 737-757.
    Link to publisher’s version
    https://doi.org/10.1007/s10479-017-2522-3
    Type
    Article
    Collections
    Management and Law Publications

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