Text as data
Next date TBD
Algorithms in Society
Next date TBD
This graduate methods course introduces students to computational text analysis, as used in the social sciences. It covers the full text-to-data-to-results pipeline, from acquisition (e.g. the use of APIs and webscraping) to pre-processing (e.g., data cleaning and formatting, supervised learning) and analyses (e.g., topic modeling, sentiment analysis, word embeddings, transformer models and text prediction). Students are expected to produce a term paper that can be developed into a publishable academic article.
In the so-called “ordinal society” of the twenty-first century, algorithmic tools that process behavioral, economic, or demographic data are widely used to compute credit scores, calculate recidivism risk, determine eligibility for welfare services, allocate police resources, curate news, personalize shopping recommendations and prices, or select matches on dating websites. Those algorithmic tools have social histories and tangible consequences in the world. They can be studied with the tools of sociology; and studying them sociologically can illuminate the intricate links between technological innovation and social organization.
Surveillance Cultures
SOC 496 (Spring 2026)
Methods of Inquiry
SOC 357 (Spring 2026)
AI and Society
(planned for Fall 2026)
This course investigates how states and corporations track, know, and govern us through the collection of personal data collection. We analyze the origins, motivations, and consequences of surveillance—from what it means to "see" like a state or market in the Information Age to how informational visibility shapes freedom, identity, and social inequality. We do this by combining empirical case studies with theoretical texts as we grapple with the importance of personal data for the making of the social order and the socially situated self.
What does it mean do to research that is social-scientific? This course introduces students to the epistemic logics and applied methodologies that underpin rigorous sociological research. You will learn about things like: designing research projects; collecting empirical data through qualitative and quantitative methods; evaluating the quality and (internal and external) validity of such data; reasoning from evidence; combining data with theory; and considering the ethical considerations of research that involves living, breathing human subjects.
We find ourselves in the middle of an AI revolution, whose impacts may eventually rival those of the Industrial Revolution. This Freshman Interest Group (FIG) seminar leverages the tools of social science—theoretical models of how societies operate, and rigorous empirical research about patterns and trends—to investigate the societal impacts of emerging (and rapidly evolving) Large Language Models. It focuses on four major themes: social/economic inequality, scientific/artistic discovery, techniques of governance, and privacy/security.