Replication Data for: CHORUS: A New Dataset of State Interest Group Policy Positions in the United States

Research on the activities and influence of interest groups in state legislatures faces a data problem: we are missing a comprehensive, systematic dataset of interest groups’ policy preferences on state legislation. We address this gap by introducing the Dataset on Policy Choice and Organizational Representation in the United States (CHORUS). This dataset compiles over 13 million policy positions stated by tens of thousands of interest groups and individuals on bills in seventeen state legislatures over the past 25 years. We describe the process used to construct CHORUS and present a new network science technique for analyzing policy position data from interest groups: the layered stochastic block model, which groups similar interest groups and bills together, respectively, based on patterns in the policy positions. Through two demonstrative applications we show the utility of these data, combined with our novel analytical approach, for understanding interest group configurations in different state legislatures and policy areas. The dataset and code here are mirrored at https://github.com/galenphall/chorus_data. While updates may continue on the main branch of the repository, the version stored here will remain available under the "review_freeze" branch.

针对州议会中利益集团的活动与影响力的相关研究面临数据困境：目前尚缺乏覆盖全面、体系化的利益集团针对州级立法的政策偏好数据集。本研究通过推出《美国政策选择与组织代表数据集》（Dataset on Policy Choice and Organizational Representation in the United States，CHORUS）填补了这一空白。该数据集收录了过去25年间，全美17个州议会中数以万计的利益集团与个人针对各类法案提出的超过1300万条政策立场。本研究阐述了CHORUS的构建流程，并提出一种用于分析利益集团政策立场数据的新型网络科学方法：分层随机块模型（layered stochastic block model），该方法可基于政策立场的模式特征，分别对相似利益集团与相似法案进行聚类。通过两项演示性应用案例，本研究验证了该数据集结合新型分析方法，在解析不同州议会与政策领域的利益集团格局方面的应用价值。本数据集及配套代码已镜像至https://github.com/galenphall/chorus_data。尽管该仓库的主分支可能仍会持续更新，但本页面存储的版本将始终保留在"review_freeze"分支下。