Porovnat metody

	UCDP Conflict Data Analysis	Event Data Analysis of Conflict
Obor	International Relations	International Relations
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	2013	1994
Tvůrce	Uppsala Conflict Data Program (Ralph Sundberg & Erik Melander for UCDP-GED)	Philip Schrodt (KEDS/TABARI); ICEWS team (Boschee et al.)
Typ	Coding and analysis of organized-violence events and conflicts	Automated extraction of structured political events from news text
Původní zdroj	Sundberg, R., & Melander, E. (2013). Introducing the UCDP Georeferenced Event Dataset. Journal of Peace Research, 50(4), 523–532.	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.
Další názvy	UCDP Analysis, UCDP Georeferenced Event Dataset Analysis, Uppsala Conflict Data Analysis, Organized Violence Event Analysis	Political Event Data, Machine-Coded Conflict Event Data, Conflict Event Extraction, Who-Did-What-to-Whom Event Coding
Příbuzné	3	4
Shrnutí	UCDP conflict data analysis is the coding and quantitative study of organized violence using the datasets of the Uppsala Conflict Data Program. UCDP distinguishes three categories of organized violence — state-based armed conflict, non-state conflict, and one-sided violence against civilians — and codes them from the level of individual fatal events up to annual conflict dyads. The Georeferenced Event Dataset (UCDP-GED), introduced by Sundberg and Melander (2013), pins each event to a place and date, enabling fine-grained spatial and temporal analysis of where and when violence occurs.	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.