For social science researchers, content analysis and classification of United States Congressional legislative activities has been time consuming and costly. The Library of Congress THOMAS system provides detailed information about bills and laws, but its classification system, the Legislative Indexing Vocabulary (LIV), is geared toward information retrieval instead of the pattern or historical trend recognition that social scientists value. The same event (a bill) may be coded with many subjects at the same time, with little indication of its primary emphasis. In addition, because the LIV system has not been applied to other activities, it cannot be used to compare (for example) legislative issue attention to executive, media, or public issue attention. This paper presents the Congressional Bills Project's (www.congressionalbills.org) automated classification system. This system applies a topic spotting classification algorithm to the task of coding legislative activities into o...