方法对比

	UCDP Conflict Data Analysis	ACLED Event Analysis
领域	International Relations	International Relations
方法族	Process / pipeline	Process / pipeline
起源年份	2013	2010
提出者	Uppsala Conflict Data Program (Ralph Sundberg & Erik Melander for UCDP-GED)	Clionadh Raleigh, Andrew Linke, Håvard Hegre & Joakim Karlsen
类型	Coding and analysis of organized-violence events and conflicts	Disaggregated coding and analysis of political-violence events
开创性文献	Sundberg, R., & Melander, E. (2013). Introducing the UCDP Georeferenced Event Dataset. Journal of Peace Research, 50(4), 523–532.	Raleigh, C., Linke, A., Hegre, H., & Karlsen, J. (2010). Introducing ACLED: An armed conflict location and event dataset. Journal of Peace Research, 47(5), 651–660.
别名	UCDP Analysis, UCDP Georeferenced Event Dataset Analysis, Uppsala Conflict Data Analysis, Organized Violence Event Analysis	ACLED Analysis, Armed Conflict Location and Event Data, Political Violence Event Analysis, Disaggregated Conflict Event Analysis
相关	3	3
摘要	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.	ACLED event analysis is the disaggregated study of political violence and protest using the Armed Conflict Location and Event Data project, introduced by Raleigh, Linke, Hegre, and Karlsen (2010). ACLED codes individual events — battles, violence against civilians, riots, protests, explosions and remote violence, and strategic developments — with their date, location, actors, and any fatalities, updated on a near-weekly basis. Its fine granularity and timeliness make it a workhorse for mapping, monitoring, and modeling where, when, and by whom political violence occurs.