Confronta i metodi

	Event Data Analysis	Analisi di sopravvivenza
Campo	Political Science	Statistica per la ricerca
Famiglia	Process / pipeline	Process / pipeline
Anno di origine	—	1958
Ideatore	Conflict-studies and computational-social-science traditions (McClelland, Schrodt, King)	Edward L. Kaplan and Paul Meier
Tipo	Automated coding and analysis of who-did-what-to-whom event records	Method
Fonte seminale	Schrodt, P. A. (2012). Precedents, Progress, and Prospects in Political Event Data. International Interactions, 38(4), 546–569.	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.
Alias	Event data coding, Political event data, Conflict event data, CAMEO event coding	Kaplan-Meier analysis, Cox regression, TTE analysis
Correlati	3	3
Sintesi	Event data analysis converts streams of news reports into structured records of political interactions — who did what to whom, when — and aggregates them into time series of cooperation and conflict between actors. Each event is coded as a source actor, an action type drawn from an ontology such as CAMEO, a target actor, and a date. Modern systems extract these events automatically from millions of news stories, enabling near-real-time measurement of interstate and intrastate behavior for forecasting and analysis.	Survival analysis is a collection of statistical methods for modeling time from a defined starting point until an event of interest occurs (disease, recovery, death, equipment failure). Kaplan and Meier's nonparametric estimator (1958) and David Cox's proportional hazards model (1972) jointly enabled analysis of censored data—individuals whose event times are unknown because they left the study or were still event-free at follow-up. Indispensable in oncology, cardiology, infectious disease research, engineering reliability, and any field where time-to-event matters.