ScholarGate
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Process / pipelineInformation extraction / NLP for political science

Event Data Analysis of Conflict

Event data analysis is the automated extraction of structured records of political interactions — who did what to whom, when, and where — from large volumes of news text, for the quantitative study of conflict and cooperation. Pioneered for machine coding by Philip Schrodt with the KEDS and TABARI systems and scaled in projects such as ICEWS and GDELT, it turns unstructured reporting into dated actor-action-target triples coded to an ontology like CAMEO, which can then be aggregated into time series of interstate or intrastate hostility.

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Fontes

  1. Schrodt, P. A., Davis, S. G., & Weddle, J. L. (1994). Political science: KEDS — A program for the machine coding of event data. Social Science Computer Review, 12(4), 561–588. See also Gerner, Schrodt et al. (1994), Machine coding of event data using regional and international sources, International Studies Quarterly, 38(1), 91–119. DOI: 10.2307/2600873
  2. Boschee, E., Lautenschlager, J., O'Brien, S., Shellman, S., Starz, J., & Ward, M. (2015). ICEWS Coded Event Data. Harvard Dataverse. DOI: 10.7910/DVN/28075

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ScholarGate. (2026, June 22). Automated Event Data Coding for the Study of Political Conflict. ScholarGate. https://scholargate.app/pt/international-relations/event-data-conflict

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ScholarGateEvent Data Analysis of Conflict (Automated Event Data Coding for the Study of Political Conflict). Recuperado em 2026-06-24 de https://scholargate.app/pt/international-relations/event-data-conflict · Conjunto de dados: https://doi.org/10.5281/zenodo.20539026