方法对比

	Cosponsorship Network Analysis	Ideal Point Estimation
领域	Political Science	Political Science
方法族	Process / pipeline	Latent structure
起源年份	2006	2004
提出者	James H. Fowler	Clinton, Jackman & Rivers (Bayesian formulation); Poole & Rosenthal (spatial tradition)
类型	Social-network analysis of legislative collaboration	Latent-variable spatial model of binary choice data
开创性文献	Fowler, J. H. (2006). Connecting the Congress: A Study of Cosponsorship Networks. Political Analysis, 14(4), 456–487.	Clinton, J., Jackman, S., & Rivers, D. (2004). The Statistical Analysis of Roll Call Data. American Political Science Review, 98(2), 355–370.
别名	Cosponsorship networks, Legislative collaboration networks, Bill cosponsorship analysis, Co-sponsorship network analysis	Ideal point model, Item response theory for roll calls, Spatial voting model, Bayesian ideal points
相关	3	4
摘要	Cosponsorship network analysis treats legislative collaboration as a social network: when legislators cosponsor one another's bills, they form ties, and the resulting web of connections can be measured with the tools of network science. Introduced to congressional studies by James Fowler in 2006, it turns the public record of who signed on to whose bills into a graph among lawmakers, revealing who is central and influential, how connected the chamber is, and which clusters of legislators form coalitions. With inferential network models such as ERGMs, researchers move from describing the network to explaining why ties form.	Ideal point estimation recovers the latent policy positions — ideal points — of political actors from their observed binary choices, most often legislators' yea/nay votes on roll calls. Building on the spatial theory of voting and formalized as a Bayesian item-response model by Clinton, Jackman, and Rivers in 2004, it places each legislator and each bill in a low-dimensional policy space and estimates positions so that the probability a legislator votes yea increases as the bill's 'yea' outcome moves closer to that legislator's ideal point.