IDEAS home Printed from https://ideas.repec.org/a/taf/ginixx/v46y2020i6p1043-1060.html
   My bibliography  Save this article

Known unknowns: media bias in the reporting of political violence

Author

Listed:
  • Nick Dietrich
  • Kristine Eck

Abstract

How does sourcing affect which events are included in international relations datasets? The increasing number of machine-coded datasets offers the promise of coding a larger corpus of documents more quickly, but existing automated processes rely exclusively on databases of news reports for coverage. We exploit source variation in the UCDP GED dataset, which includes events from media reports and non-media sources, to explore the bias introduced by including only media reports in international relations datasets. Unlike previous studies, our approach allows us to compare subnational and cross-national determinants of bias. We find that media sources severely underreport events in African countries, and coverage is also associated with country-level factors like international trade and subnational factors like access to communication technology. Non-media sources cover a significant number of events not included in media sources; their inclusion can expand coverage and reduce bias in datasets.

Suggested Citation

  • Nick Dietrich & Kristine Eck, 2020. "Known unknowns: media bias in the reporting of political violence," International Interactions, Taylor & Francis Journals, vol. 46(6), pages 1043-1060, November.
  • Handle: RePEc:taf:ginixx:v:46:y:2020:i:6:p:1043-1060
    DOI: 10.1080/03050629.2020.1814758
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03050629.2020.1814758
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03050629.2020.1814758?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.

    Citations

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


    Cited by:

    1. Hanne Fjelde & Kristine Höglund, 2022. "Introducing the Deadly Electoral Conflict Dataset (DECO)," Journal of Conflict Resolution, Peace Science Society (International), vol. 66(1), pages 162-185, January.
    2. Lewis, Janet I., 2023. "Rebel group formation in Africa: Evidence from a new dataset," World Development, Elsevier, vol. 170(C).

    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:taf:ginixx:v:46:y:2020:i:6:p:1043-1060. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GINI20 .

    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.