John Wilkerson

Also published as: John D. Wilkerson


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Overview of the 2014 NLP Unshared Task in PoliInformatics
Noah A. Smith | Claire Cardie | Anne Washington | John Wilkerson
Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science


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Textual Predictors of Bill Survival in Congressional Committees
Tae Yano | Noah A. Smith | John D. Wilkerson
Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies


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The U.S. Policy Agenda Legislation Corpus Volume 1 - a Language Resource from 1947 - 1998
Stephen Purpura | John Wilkerson | Dustin Hillard
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

We introduce the corpus of United States Congressional bills from 1947 to 1998 for use by language research communities. The U.S. Policy Agenda Legislation Corpus Volume 1 (USPALCV1) includes more than 375,000 legislative bills annotated with a hierarchical policy area category. The human annotations in USPALCV1 have been reliably applied over time to enable social science analysis of legislative trends. The corpus is a member of an emerging family of corpora that are annotated by policy area to enable comparative parallel trend recognition across countries and domains (legislation, political speeches, newswire articles, budgetary expenditures, web sites, etc.). This paper describes the origins of the corpus, its creation, ways to access it, design criteria, and an analysis with common supervised machine learning methods. The use of machine learning methods establishes a baseline proposed modeling for the topic classification of legal documents.