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Terrorism in armed conflict: new data attributing terrorism to rebel organizations

Author

Listed:
  • Virginia Page Fortna

    (Columbia University, USA)

  • Nicholas J. Lotito

    (Yale University, USA)

  • Michael A. Rubin

    (University of Connecticut, Human Rights Institute, USA)

Abstract

The Terrorism in Armed Conflict project integrates the Uppsala Conflict Data Project sample of rebel organizations with START’s Global Terrorism Database, covering 409 organizations for 1970–2013. For many Global Terrorism Database incidents, perpetrator information is missing, or ambiguous. Because the accuracy of perpetrator information likely varies systematically, simply dropping these incidents from analyses may bias results. Terrorism in Armed Conflict provides possible attribution to specific rebel groups with coding for uncertainty, enabling researchers to (1) address “description bias†in media-based terrorism data, (2) model uncertainty regarding perpetrator attribution and (3) vary the way terrorism is counted. The Terrorism in Armed Conflict dataset further provides a measure of deliberately indiscriminate terrorism that allows for more nuanced testing of arguments about the strategic logic of terrorism.

Suggested Citation

  • Virginia Page Fortna & Nicholas J. Lotito & Michael A. Rubin, 2022. "Terrorism in armed conflict: new data attributing terrorism to rebel organizations," Conflict Management and Peace Science, Peace Science Society (International), vol. 39(2), pages 214-236, March.
  • Handle: RePEc:sae:compsc:v:39:y:2022:i:2:p:214-236
    DOI: 10.1177/0738894220972996
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    References listed on IDEAS

    as
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    4. Nils B. Weidmann, 2016. "A Closer Look at Reporting Bias in Conflict Event Data," American Journal of Political Science, John Wiley & Sons, vol. 60(1), pages 206-218, January.
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