All students must meet the Requirements for the Doctor of Philosophy Degree
Overview
The Ph.D. program in Computational Studies of Culture and Society is an interdisciplinary program that grounds students in the theories and methods of the arts, humanities, and social sciences while training them in complex systems—preparing critical thinkers to engage with large-scale social problems using the tools of computational analysis.
Students are trained in the use of computational and qualitative methods in order to ask critically engaged questions around culture, society, and human behaviors. The program’s core curriculum provides students with theoretical grounding from a humanities and social scientific perspective, as well as the computational skills needed for analysis of large-scale data sets.
Balancing a structured core curriculum with elective courses, students gain the content-specific knowledge and area specializations necessary to carry out meaningful research in culture and society using computational techniques. They also develop the technical expertise for data mining and engaging with large language model methodologies (among other tools), while remaining rooted in intellectual traditions that engage social theory in the interpretation of results. The program trains students to translate their findings across traditional disciplinary boundaries in order for their work to impact the widest possible audience.
Specific Requirements
Minimum Degree Requirements
A minimum of 75 credits are required, of which at least 33 must be graded graduate coursework credits and at least 30 must be research credits. Graduate elective credits should be chosen in consultation with the student’s advisor. Students who have not met the prerequisites for the Complex Systems core courses (CSYS 5870, CSYS 6701, CSYS 6713, CSYS 6020) may need to take MATH 2522, CS 2240, and/or STAT 1410; completing these courses will not count towards the required 75 credits. Students may, with the approval of their advisor and their graduate studies committee, substitute a graduate elective for CSYS 6713/CSYS 6020.
| Requirement Description | Credits | |
|---|---|---|
| Core requirements (24 Credits) | ||
| CSYS 5870 | Data Science I | 3 |
| CSYS 6701 | Principles of Complex Systms 1 | 3 |
| CSYS 6713 | Principles of Complex Systms 2 | 3 |
| or CSYS 6020 | Modeling Complex Systems I | |
| CSCS 7010 | Computational Hu&SocSc1 | 3 |
| CSCS 7020 | Computational Hu&SocScII | 3 |
| CSCS 6110 | Ethics in Computational Hum | 3 |
| CSCS 6200 | Qualitative Methods in CSCS | 3 |
| CSCS 7100 | CSCS Professional Seminar | 3 |
| Elective pathways (9–21 credits) | ||
Elective courses to be chosen in consultation with the advisor. Sample elective pathways include Critical Approaches to Health; Food Systems Agriculture and the Environment; Critical Approaches to Image, Text, and Culture; etc. | ||
| Research Requirements (30-42 credits) | ||
| Doctoral Dissertation Research (at least 20 credits) | ||
| Internship | ||
Comprehensive Examination
The comprehensive examination is a tool to evaluate the progress of each student and ensure that they are prepared to proceed towards the doctorate degree.
The comprehensive examination will have a written and an oral component to it. The written component will include the assessment of a portfolio that the student will compile based on their internship and other materials that showcase their work and areas of sustained interest. The oral component will consist of the student defending their written examination and demonstrating their knowledge of a broad range of concepts in the student’s discipline.
Requirements for Advancement to Candidacy for the Degree of Doctor of Philosophy
Students will advance to candidacy upon successful completion of all required courses, passage of the written and oral comprehensive examinations, and successful oral defense of the dissertation proposal.