方法对比

	Content Analysis of Treaties	Event Data Analysis of Conflict
领域	International Relations	International Relations
方法族	Process / pipeline	Process / pipeline
起源年份	2000	1994
提出者	Klaus Krippendorff (content analysis methodology); legalization literature (Abbott et al.)	Philip Schrodt (KEDS/TABARI); ICEWS team (Boschee et al.)
类型	Systematic coding of the text and design features of international agreements	Automated extraction of structured political events from news text
开创性文献	Hayes, A. F., & Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures, 1(1), 77–89.	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.
别名	Treaty Text Analysis, International Agreement Coding, Treaty Design Content Analysis, Legalization Content Analysis	Political Event Data, Machine-Coded Conflict Event Data, Conflict Event Extraction, Who-Did-What-to-Whom Event Coding
相关	3	4
摘要	Content analysis of treaties is the systematic, rule-governed coding of the text and design features of international agreements — their obligations, precision, delegation, enforcement, flexibility, and substantive provisions — to study how treaties are written and what explains variation in their design. It applies the established content-analysis methodology codified by Krippendorff to the specialized vocabulary of international law and institutions, often organized around frameworks such as the legalization concept of Abbott and colleagues (2000).	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.