Computational Social Science
In the Computational Social Sciences (CSS) program, you’ll explore the intersection of technology, society and humanity. Harnessing computational tools for data visualization and analysis, you’ll discover applications for academic research and industry. Uncover patterns in collective behavior to address real-world challenges like inequality, climate change, and public policy, driving smarter solutions for business, society, and global collaboration. Launches Fall 2025.
Program Overview
The Computational Social Science (CSS) program equips students with the skills to analyze human social and behavioral data, uncover patterns, and address contemporary challenges in public policy, business, and society. Ideal for those drawn to problem-solving through data and social science, this program combines coursework in computational tools, data visualization, and foundational social, political, and economic concepts. Students will gain real-world skills applicable to diverse fields, from public health and social media analysis to marketing, sports statistics, and trend forecasting. The 30-credit CSS major includes foundational courses in computational and statistical methods, as well as advanced electives spanning geography, anthropology, psychology, and more. For students seeking a focused exploration, the 15-credit CSS minor emphasizes core knowledge, analysis, and application in the field.
Program Requirements
- Major Requirements (to be published soon)
- Minor Requirements
Why Computational Social Science?
The CSS major or minor will prepare students to understand, engage with, and solve evolving, complex challenges such as climate change, social polarization, and inequality. By learning coding languages to analyze and visualize large data sets, students will gain the capacity to explore their interests using the data sources that surround us. Making your own discoveries, uncovering patterns and finding innovate solutions is central to computational social science. Graduates will enter a fast-growing, field with real impact on the world.
Combining core CSS skills and interdisciplinary electives, students gain real-world experience and the flexibility to tailor their education while tackling issues ranging from public health to AI’s societal impacts. Through small class sizes, personalized mentorship, and collaborative research opportunities, students graduate as leaders ready to address complex socio-economic and environmental challenges, foster smart governance and informed public engagement and discourse.
At UT and beyond, CSS graduates will lead efforts to inform policy decisions, spark public engagement, and improve science communication, while advancing smart governance, equitable decision-making, and the flow of information between science and society. With their ability to analyze and address how socio-economic disparities become entrenched in institutional norms, CSS graduates will enter fields like municipal government, public policy, and global innovation.
Careers
The job market for Computational Social Sciences (CSS) is rapidly expanding across business, government, academia, and research. CSS research centers are being launched at leading universities globally, reflecting the field’s growing influence.
Graduates of CSS programs are highly employable, with career opportunities in roles like data scientist, social policy analyst, market analyst, and public health data strategist. Employers range from tech giants like Google, which uses CSS to address the societal impacts of AI, to government agencies shaping policy, non-profits driving social change, and consulting firms like McKinsey and Deloitte. According to the U.S. Bureau of Labor Research, employment in the broader computational and data science sector is growing at 5 percent annually, with an average salary of more than $100,000.
Featured Courses
COSC 111
Computational Thinking and the Art of Programming
3 credit hours. Think algorithmically and solve problems using a programming language, software and technologies. No prerequisite.
DATA 101
Data Knowledge and Discovery
3 credit hours. Introduction to the essential elements of data science. Explores data collection and management, exploration and visualization of data, and data ethics. Introduces students to programming through hands-on activities.
CSS 201
Computational Social Science
3 credit hours. Analyze, visualize data on social and cultural change, from ancient to contemporary societies and social media. Learn programming in R. No prerequisite.
INSC 260
Programming for Information Applications
3 credit hours. Programming languages, data structures & func- tions for processing and visualizing data. No prerequisite.
HBS 301
Thinking Analytically
3 credit hours. Analytical thinking in econometrics based on data collection, analysis, and interpretation. No prerequisite.
INSC 489
Information Visualization
3 credit hours. Visual, intuitive and interactive representation of various types of data. Prerequisite: INSC 260.