IDEAS home Printed from https://ideas.repec.org/a/eee/ininma/v61y2021ics0268401221000906.html
   My bibliography  Save this article

The effect of toxicity on COVID-19 news network formation in political subcommunities on Reddit: An affiliation network approach

Author

Listed:
  • Chipidza, Wallace

Abstract

Political polarization remains perhaps the “greatest barrier” to effective COVID-19 pandemic mitigation measures in the United States. Social media has been implicated in fueling this polarization. In this paper, we uncover the network of COVID-19 related news sources shared to 30 politically biased and 2 neutral subcommunities on Reddit. We find, using exponential random graph modeling, that news sources associated with highly toxic – “rude, disrespectful” – content are more likely to be shared across political subreddits. We also find homophily according to toxicity levels in the network of online news sources. Our findings suggest that news sources associated with high toxicity are rewarded with prominent positions in the resultant network. The toxicity in COVID-19 discussions may fuel political polarization by denigrating ideological opponents and politicizing responses to the COVID-19 pandemic, all to the detriment of mitigation measures. Public health practitioners should monitor toxicity in public online discussions to familiarize themselves with emerging political arguments that threaten adherence to public health crises management. We also recommend, based on our findings, that social media platforms algorithmically promote neutral and scientific news sources to reduce toxic discussion in subcommunities and encourage compliance with public health recommendations in the fight against COVID-19.

Suggested Citation

  • Chipidza, Wallace, 2021. "The effect of toxicity on COVID-19 news network formation in political subcommunities on Reddit: An affiliation network approach," International Journal of Information Management, Elsevier, vol. 61(C).
  • Handle: RePEc:eee:ininma:v:61:y:2021:i:c:s0268401221000906
    DOI: 10.1016/j.ijinfomgt.2021.102397
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0268401221000906
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijinfomgt.2021.102397?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:eee:ininma:v:61:y:2021:i:c:s0268401221000906. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-information-management .

    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.