Marinov will speak about a number of applications of text analysis to issues in comparative politics and international relations. One is a an original dataset of economic sanctions, and discussion of economic sanctions, generated by applying machine-learning methods to U.S. Congressional documents and Presidential statements. A related one is using a variety of techniques, including named-entity recognition, to understand when American policy-makers discuss other countries’ elections, leaders, human rights and commitments to international treaties. A third application concerns how to link up all this information to information available on the web on countries’ elections, including information on who ran and on how competitive the election was. The result is a new body of data, uniquely suited to answer questions of interest to political scientists of all stripes, including questions about American foreign policy, sources of influence on other countries’ human rights, and on the electoral outcomes we observe around the world.