Context: The State of the Union is an annual address by the President of the United States before a joint session of congress. In it, the President reviews the previous year and lays out his legislative agenda for the coming year. Content: This dataset contains the full text of the State of the Union address from 1989 (Regan) to 2017 (Trump). Inspiration: This is a nice, clean set of texts perfect for exploring Natural Language Processing techniques * Topic modelling: Which topics have become more popular over time? Which have become less popular? * Sentiment analysis: Are there differences in tone between different Presidents? Presidents from different parties? * Parsing: Can you train implement a parser to automatically extract the syntactic relationships between words? * Authorship identification: Can you correctly identify the author of a previously unseen address?