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The MID5 Dataset, 2011–2014: Procedures, coding rules, and description

Author

Listed:
  • Glenn Palmer

    (The Pennsylvania State University, USA)

  • Roseanne W McManus

    (The Pennsylvania State University, USA)

  • Vito D’Orazio

    (University of Texas at Dallas, USA)

  • Michael R Kenwick

    (Rutgers University, USA)

  • Mikaela Karstens

    (The Pennsylvania State University, USA)

  • Chase Bloch

    (The Pennsylvania State University, USA)

  • Nick Dietrich

    (Ohio Wesleyan University, USA)

  • Kayla Kahn

    (The Pennsylvania State University, USA)

  • Kellan Ritter

    (The Pennsylvania State University, USA)

  • Michael J Soules

    (The Pennsylvania State University, USA)

Abstract

This article introduces the latest iteration of the most widely used dataset on interstate conflicts, the Militarized Interstate Dispute (MID) 5 dataset. We begin by outlining the data collection process used in the MID5 project. Next, we discuss some of the most challenging cases that we coded and some updates to the coding manual that resulted. Finally, we provide descriptive statistics for the new years of the MID data.

Suggested Citation

  • Glenn Palmer & Roseanne W McManus & Vito D’Orazio & Michael R Kenwick & Mikaela Karstens & Chase Bloch & Nick Dietrich & Kayla Kahn & Kellan Ritter & Michael J Soules, 2022. "The MID5 Dataset, 2011–2014: Procedures, coding rules, and description," Conflict Management and Peace Science, Peace Science Society (International), vol. 39(4), pages 470-482, July.
    • Handle: RePEc:sae:compsc:v:39:y:2022:i:4:p:470-482
    DOI: 10.1177/0738894221995743
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    References listed on IDEAS

    as
    1. Vito D’Orazio & Michael Kenwick & Matthew Lane & Glenn Palmer & David Reitter, 2016. "Crowdsourcing the Measurement of Interstate Conflict," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-21, June.
    2. D'Orazio, Vito & Landis, Steven T. & Palmer, Glenn & Schrodt, Philip, 2014. "Separating the Wheat from the Chaff: Applications of Automated Document Classification Using Support Vector Machines," Political Analysis, Cambridge University Press, vol. 22(2), pages 224-242, April.
    Full references (including those not matched with items on IDEAS)

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