College Minor

Computational Social Science is an emergent field at the intersection of the social and computational sciences – leveraging computational advances, such as those in AI and Machine Learning, as well as the widespread availability of “big data,” to drive the next generation of social research.

The Minor in Computational Social Science enables College students in the social sciences to build fundamental computational skills with the purpose of enriching existing approaches to social scientific inquiry. Additionally, for College students outside of the social sciences (e.g., in the physical and biological sciences), it provides an opportunity to consolidate their computational, mathematical, and statistical skills, as well as apply these skills to questions about social and cultural life.

Over the course of the program, students will learn how computational approaches complement and expand upon traditional research designs in the social sciences, as well as gain the hands-on computer programming and data analysis skills necessary to implement these computationally-enhanced research designs. For instance, students will learn how “big data” and AI technologies enhance traditional observational studies, explore simulation-based research designs, as well as investigate how to run large, computationally-enhanced surveys and digital experiments. They will additionally have the opportunity to explore advanced approaches for applying their computational and analytical skills to social science problems in elective courses in Computational Social Science. For example, students may complete Machine Learning and High-Performance Computing coursework, with an emphasis on applicability to social scientific research.

In completing the minor requirements, students will also meet many of the requirements for admission into the MA Program in Computational Social Science (MACSS), as a part of the Advanced Scholars “4+1” Program. Students who are admitted into the program can earn a MA degree in Computational Social Science with only one additional year of study beyond their undergraduate coursework. Students interested in pursuing a College Minor en route to a MA in Computational Social Science are encouraged to reach out to the Associate Director of Undergraduate Studies, Jon Clindaniel, for more information on recommended undergraduate course planning leading up to their “+1” year.

Minor Requirements

The minor consists of six courses: one course introducing contemporary approaches for performing Computational Social Science research, one data analysis course, two computational methods courses, and two electives in Computational Social Science.

Courses in the minor must be taken for quality grades and may not be double counted with the student’s major(s), other minors, or general education requirements.

Students who wish to declare a minor in Computational Social Science must reach out to the Associate Director for Undergraduate Studies, Jon Clindaniel, to indicate their intention to complete the minor and have their Consent to Complete a Minor Program form signed. Students will need to submit the signed form to their College Adviser before the end of the Spring Quarter of their third year.

Students interested in receiving email updates with information about courses, events, and opportunities relevant to the Computational Social Science Minor Program can sign up to join our list host here. Students are also encouraged to reach out to Jon Clindaniel to meet and discuss course plans, as well as obtain advice relevant to their interests.

Summary of Requirements

Course ID Course Units
MACS 10000 Perspectives on Computational Analysis 100
STAT 22000 Statistical Methods and Applications (or approved equivalent coursework in data analysis) * 100
MACS 10111 & 10112 Principles of Computing 1: Computational Thinking for Social Scientists & Principles of Computing 2: Data Management for Social Scientists (or approved equivalent coursework in computational methods) 200
Two Computational Social Science Electives (any two courses with a MACS course number at the 20000-level and below) 200
Total Units 600

* Students who take STAT 22000 or equivalent coursework for their major, another minor, or general education requirement will complete a five-course (500-unit) minor

Approved Equivalent Coursework in Data Analysis

If students have not already completed a statistics or data analysis course for their major, another minor, or general education requirement, they must complete such a course for the Computational Social Science minor. Specifically, students should complete STAT 22000 “Statistical Methods and Applications” or equivalent coursework (at the same or higher level of mathematical requirements).

Examples of approved equivalent coursework include (students should complete the course specific to their major, other minor, or general education requirements):

  • Higher level foundational STAT courses:
    • STAT 23400 “Statistical Models and Methods”
    • STAT 24400 “Statistical Theory and Methods”
  • DATA 11900 “Introduction to Data Science II”
  • Other statistics offerings within the Social Sciences Division:
    • CHDV 20101 “Applied Statistics in Human Development Research”
    • ECON 11010 “Introduction to Statistical Methods in Economics”
    • ECON 21010 “Statistical Methods in Economics”
    • PSYC 20250 “Introduction to Statistical Concepts and Methods”
    • SOCI 20004 “Statistical Methods of Research”
    • SOSC 26009 “Introductory Statistical Methods”
  • Other approved substitutions by petition

Approved Equivalent Coursework in Computational Methods

Students must complete two introductory computer programming courses: MACS 10111 “Principles of Computing 1: Computational Thinking for Social Scientists” and MACS 10112 “Principles of Computing 2: Data Management for Social Scientists,” or equivalent coursework.

  • CMSC 12100 & 12200 “Computer Science with Applications I” & “Computer Science with Applications II”
  • CMSC 14100 & 14200 “Introduction to Computer Science I” & “Introduction to Computer Science II”
  • If students have already completed introductory computer programming courses (e.g. CMSC 14100-14200) as a part of their major, another minor, or general education requirements, they may substitute additional CMSC or MACS courses to meet the two-course Computational Methods minor requirement. For instance, a student who completed CMSC 14100-14200 to meet requirements in their major might take MACS 10113 “Principles of Computing 3: Big Data and High Performance Computing for Social Scientists” and CMSC 14300 “Systems Programming I” to meet the requirements (or any other combination of CMSC and MACS courses) of the minor.
  • Other approved substitutions by petition

Computational Social Science Elective Options

Students must complete at least two Computational Social Science electives as a part of the minor – any two Computational Social Science courses with a MACS course number at the 20000-level and below (a list of all MACS courses offered is available by clicking the “Courses” tab, or going to the Schedule of Classes and searching “MACS” for the most up-to-date information each quarter). Course availability varies by year.