This course explores the application of natural language processing techniques to texts in law, politics, and the news media.
Learning objective
Students will be introduced to a broad array of tools in natural language processing (NLP). They will learn to evaluate and apply NLP tools to a variety of problems. The applications will focus on social-science contexts, including law, politics, and the news media. Topics include text classification, topic modeling, transformers, model explanation, and bias in language.
Content
NLP technologies have the potential to assist judges and other decision-makers by making tasks more efficient and consistent. On the other hand, language choices could be biased toward some groups, and automated systems could entrench those biases.
We will explore the use of NLP for social science research, not just in the law but also in politics, the economy, and culture. We will explore, critique, and integrate the emerging set of tools for debiasing language models and think carefully about how notions of fairness should be applied in this domain.
Prerequisites / Notice
Some programming experience in Python is required, and some experience with NLP is highly recommended.
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course