My research applies machine learning and deep neural networks to analyzing political texts. My approach combines concern for design-based causal inference, generation of new sources of data, and new techniques for analyzing them to answer important political questions, such as uncovering undisclosed political spending among nonprofits and measuring Parliamentary polarization and ideology.