IDEAS home Printed from https://ideas.repec.org/a/sae/compsc/v39y2022i4p470-482.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0738894221995743
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0738894221995743?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
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sandra Wankmüller, 2023. "A comparison of approaches for imbalanced classification problems in the context of retrieving relevant documents for an analysis," Journal of Computational Social Science, Springer, vol. 6(1), pages 91-163, April.
    2. Juhász, Réka & Lane, Nathaniel & Oehlsen, Emily & Pérez, Verónica C., 2022. "The Who, What, When, and How of Industrial Policy: A Text-Based Approach," SocArXiv uyxh9, Center for Open Science.
    3. Zhanna Terechshenko, 2020. "Hot under the collar: A latent measure of interstate hostility," Journal of Peace Research, Peace Research Institute Oslo, vol. 57(6), pages 764-776, November.
    4. Sara Kahn-Nisser, 2019. "When the targets are members and donors: Analyzing inter-governmental organizations’ human rights shaming," The Review of International Organizations, Springer, vol. 14(3), pages 431-451, September.
    5. Juan D Botero & Weisi Guo & Guillem Mosquera & Alan Wilson & Samuel Johnson & Gicela A Aguirre-Garcia & Leonardo A Pachon, 2019. "Gang confrontation: The case of Medellin (Colombia)," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-19, December.
    6. 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.
    7. Glenn Palmer & Vito D’Orazio & Michael Kenwick & Matthew Lane, 2015. "The MID4 dataset, 2002–2010: Procedures, coding rules and description," Conflict Management and Peace Science, Peace Science Society (International), vol. 32(2), pages 222-242, April.
    8. Michael R Kenwick & Beth A Simmons & Richard J McAlexander, 2024. "Infrastructure and authority at the state’s edge: The Border Crossings of the World dataset," Journal of Peace Research, Peace Research Institute Oslo, vol. 61(3), pages 500-510, May.

    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:sae:compsc:v:39:y:2022:i:4:p:470-482. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: SAGE Publications (email available below). General contact details of provider: http://pss.la.psu.edu/ .

    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.