Võrdle meetodeid

	Power Transition Analysis	Event Data Analysis of Conflict
Valdkond	International Relations	International Relations
Perekond	Process / pipeline	Process / pipeline
Tekkeaasta	1980	1994
Looja	A. F. K. Organski & Jacek Kugler	Philip Schrodt (KEDS/TABARI); ICEWS team (Boschee et al.)
Tüüp	Theory-driven observational analysis of war between rising and dominant powers	Automated extraction of structured political events from news text
Algallikas	Organski, A. F. K., & Kugler, J. (1980). The War Ledger. University of Chicago Press.	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.
Rööpnimetused	Power Transition Theory Analysis, Power Parity and War Analysis, Hegemonic Transition Analysis, Overtaking and War Analysis	Political Event Data, Machine-Coded Conflict Event Data, Conflict Event Extraction, Who-Did-What-to-Whom Event Coding
Seotud	3	4
Kokkuvõte	Power transition analysis examines when and why war breaks out between a dominant state and a rising challenger as their relative power converges. Originating in A. F. K. Organski and Jacek Kugler's The War Ledger (1980), it holds that the international system is hierarchical and most dangerous not at moments of clear preponderance but when a dissatisfied rising power approaches parity with the dominant state — and it operationalizes this by tracking relative national capabilities over time and relating overtaking to the onset of major war.	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.