IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/8180272.html
   My bibliography  Save this article

Predicting Social Unrest Events with Hidden Markov Models Using GDELT

Author

Listed:
  • Fengcai Qiao
  • Pei Li
  • Xin Zhang
  • Zhaoyun Ding
  • Jiajun Cheng
  • Hui Wang

Abstract

Proactive handling of social unrest events which are common happenings in both democracies and authoritarian regimes requires that the risk of upcoming social unrest event is continuously assessed. Most existing approaches comparatively pay little attention to considering the event development stages. In this paper, we use autocoded events dataset GDELT (Global Data on Events, Location, and Tone) to build a Hidden Markov Models (HMMs) based framework to predict indicators associated with country instability. The framework utilizes the temporal burst patterns in GDELT event streams to uncover the underlying event development mechanics and formulates the social unrest event prediction as a sequence classification problem based on Bayes decision. Extensive experiments with data from five countries in Southeast Asia demonstrate the effectiveness of this framework, which outperforms the logistic regression method by 7% to 27% and the baseline method 34% to 62% for various countries.

Suggested Citation

  • Fengcai Qiao & Pei Li & Xin Zhang & Zhaoyun Ding & Jiajun Cheng & Hui Wang, 2017. "Predicting Social Unrest Events with Hidden Markov Models Using GDELT," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-13, May.
    • Handle: RePEc:hin:jnddns:8180272
    DOI: 10.1155/2017/8180272
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/DDNS/2017/8180272.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/DDNS/2017/8180272.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/8180272?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
    ---><---

    Citations

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


    Cited by:

    1. Jin, Xuejun & Chen, Cheng & Yang, Xiaolan, 2024. "The effect of international media news on the global stock market," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 50-69.
    2. Elizabeth Gooch & Stone Goethe & Nicholas Sobrepena & Eric Eckstrand, 2022. "Measuring competition between the great powers across Africa and Asia using a measure of relative dispersion in media coverage bias," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    3. Barrett, Philip & Appendino, Maximiliano & Nguyen, Kate & de Leon Miranda, Jorge, 2022. "Measuring social unrest using media reports," Journal of Development Economics, Elsevier, vol. 158(C).
    4. Yunxing Yao & Yinbao Zhang & Jianzhong Liu & Yanpei Li & Xiaopei Li, 2022. "Analysis of Spatiotemporal Characteristics and Influencing Factors for the Aid Events of COVID-19 Based on GDELT," Sustainability, MDPI, vol. 14(19), pages 1-18, September.

    More about this item

    Statistics

    Access and download statistics

    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:hin:jnddns:8180272. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.