State legislatures often rely on existing text when drafting new bills. Resource and expertise constraints, which often drive this copying behavior, can be taken advantage of by lobbyists and special interest groups. These groups provide model bills, which encode policy agendas, with the intent that the models become actual law. Unfortunately, model legislation is often opaque to the public-both in source and content. In this paper we present LobbyBack, a system that reverse engineers model legislation from observed text. LobbyBack identifies clusters of bills which have text reuse and generates "prototypes" that represent a canonical version of the text shared between the documents. We demonstrate that LobbyBack accurately reconstructs model legislation and apply it to a dataset of over 550k bills.

Pre-print: PDF (480Kb), to appear, ACL 2016