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 LOBBY-BACK accurately reconstructs model legislation and apply it to a dataset of over 550k bills.

State legislatures introduce at least 45,000 bills each year. However, we lack a clear understanding of who is actually writing those bills. As legislators often lack the time and staff to draft each bill, they frequently copy text written by other states or interest groups. However, existing approaches to detect text reuse are slow, biased, and incomplete. Journalists or researchers who want to know where a particular bill originated must perform a largely manual search. Watchdog organizations even hire armies of volunteers to monitor legislation for matches. Given the time-consuming nature of the analysis, journalists and researchers tend to limit their analysis to a subset of topics (e.g. abortion or gun control) or a few interest groups.