IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-33-4359-7_44.html
   My bibliography  Save this book chapter

Mining and Analysis of Emergency Information on Social Media

In: Liss 2020

Author

Listed:
  • Dan Chang

    (Beijing Jiaotong University)

  • Lizhu Cui

    (Beijing Jiaotong University)

  • Yiming Sun

    (The University of Melbourne)

Abstract

With the advent of the social media era, various social networking sites and social apps are growing at a high speed. As an important product of the WEB 2.0 era, Sina microblog has become an important vehicle for the dissemination of emergency information. In this paper, the textual features of microblogging are first analyzed and then text pre-processed based on the emergency response information of the microblog platform. Based on this, an MB-LDA (MicroBlog-Latent Dirichlet Allocation) topic model based on the “User-Document-Topic-Word” structure is proposed. The aim is to improve the government's ability to respond to emergencies and to improve the efficiency of government emergency information collection by thematically mining and analyzing emergency information in case of emergencies, so as to obtain the actual situation of emergencies and other effective emergency information.

Suggested Citation

  • Dan Chang & Lizhu Cui & Yiming Sun, 2021. "Mining and Analysis of Emergency Information on Social Media," Springer Books, in: Shifeng Liu & Gábor Bohács & Xianliang Shi & Xiaopu Shang & Anqiang Huang (ed.), Liss 2020, pages 627-648, Springer.
  • Handle: RePEc:spr:sprchp:978-981-33-4359-7_44
    DOI: 10.1007/978-981-33-4359-7_44
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Ning Hu & Kee Chye Ho & Pik Shy Fan, 2024. "Malaysian Chinese folk beliefs on Facebook based on LDA topic modelling," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.

    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:sprchp:978-981-33-4359-7_44. 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.