The Congress Viewer (years 1900 - 2000), a prototype text mining app, demonstrates the potential of tools designed to measure lexical changes, including advanced NLP techniques like parsing and analyzing grammatical relationships. This app can increase transparency in Congress while also providing new insights into the evolution and nature of political language across various contexts, including different time periods and discourse communities.
Use an array of data-mining and statistical approaches to gain new insights into the evolution and nature of political language as it occurs in different time periods and in different contexts.
Computational methods are changing the way that we access information about history and society. These methods help us to detect change over time, to identify influential figures, and to name turning points. What happens when we apply these tools to the entire Hansard corpus or to a million congressional debates and tweets? This work provides an introduction to the analytic methodologies transforming the humanities and social sciences via a book, under contract at Cambridge University Press, and series of Jupyter Notebooks aimed at exploring questions like these.
