IDEAS home Printed from https://ideas.repec.org/a/wsi/jikmxx/v20y2021i03ns0219649221500386.html
   My bibliography  Save this article

An Evolutionary Clustering Analysis of Social Media Content and Global Infection Rates During the COVID-19 Pandemic

Author

Listed:
  • Ibrahim Arpaci

    (Department of Computer Education and Instructional Technology, Tokat Gaziosmanpasa University, 60250 Tokat, Turkey)

  • Shadi Alshehabi

    (Department of Computer Engineering, Turkish Aeronautical Association University, Etimesgut, 06790 Ankara, Turkey)

  • Ibrahim Mahariq

    (College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait)

  • Ahmet E. Topcu

    (College of Engineering and Technology, American University of the Middle East, Egaila, Kuwait)

Abstract

This study investigates the impact of global infection rates on social media posts during the COVID-19 pandemic. The study analysed over 179 million tweets posted between March 22 and April 13, 2020 and the global COVID-19 infection rates using evolutionary clustering analysis. Results showed six clusters constructed for each term type, including three-level n-grams (unigrams, bigrams and trigrams). The frequent occurrences of unigrams (“COVID-19”, “virus”, “government”, “people”, etc.), bigrams (“COVID 19”, “COVID-19 cases”, “times share”, etc.) and trigrams (“COVID 19 crisis”, “things help stop” and “trying times share”) were identified. The results demonstrated that the unigram trends on Twitter were up to about two times and 54 times more common than the bigram terms and trigram terms, respectively. Unigrams like “home” or “need” also became important as these terms reflected the main concerns of people during this period. Taken together, the present findings confirm that many tweets were used to broadcast people’s prevalent topics of interest during the COVID-19 pandemic. Furthermore, the results indicate that the number of COVID-19 infections had a significant effect on all clusters, being strong on 86% of clusters and moderate on 16% of clusters. The downward slope in global infection rates reflected the start of the trending of “social distancing” and “stay at home”. These findings suggest that infection rates have had a significant impact on social media posting during the COVID-19 pandemic.

Suggested Citation

  • Ibrahim Arpaci & Shadi Alshehabi & Ibrahim Mahariq & Ahmet E. Topcu, 2021. "An Evolutionary Clustering Analysis of Social Media Content and Global Infection Rates During the COVID-19 Pandemic," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-18, September.
    • Handle: RePEc:wsi:jikmxx:v:20:y:2021:i:03:n:s0219649221500386
    DOI: 10.1142/S0219649221500386
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219649221500386
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219649221500386?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.

    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:wsi:jikmxx:v:20:y:2021:i:03:n:s0219649221500386. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/jikm/jikm.shtml .

    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.