Complex Socio-Technical Systems
Socio-technical systems are all around us. By analyzing them, we come closer to understanding ourselves.
We live and work in complex, adaptive and evolving socio-technical systems. This expansive and interdependent web of technology and social interaction gives rise to a number of complex challenges from both technical and social perspectives. A simple example can be taken from social media: How do social networking platforms, like Facebook and Twitter, change in response to the ways in which users interact with them? In turn, how are social structures shaped through the technical structure of the platforms themselves?
The opportunities to examine the relationships between technology and the social consequences to which it gives rise is vast. And our research in Complex Socio-Technical Systems brings together a renowned set of cross-disciplinary faculty to address these questions using tools and methods drawn from network science, social network analysis, big data analytics, statistical analysis, and the social sciences.
In the Societal Computing PhD program at Carnegie Mellon University, our research in complex socio-technical systems leverages computational methods to understand and influence large-scale social systems. Our work spans critical areas like online social behavior, privacy and security, social network dynamics, text analysis, and understanding socio-technical systems, preparing students to tackle real-world challenges at the intersection of technology and society.
Software is in everything. Software shapes the digital enviornment, which shapes how we find information, conduct commerce, share and socialize, do our work, and amuse ourselves.
Social cybersecurity: an emerging science
Tackles online misinformation and influence operations with cutting-edge computational tools.
Work with Kathleen M. Carley to combat online misinformation and influence operations using advanced computational tools. Join this fight against digital threats.
Adding Sparkle to Social Coding: An Empirical Study of Repository Badges in the npm Ecosystem
Explores how badges improve trust and quality in open source software communities.
When and how to make breaking changes: Policies and practices in 18 open source software ecosystems
Examines strategies for managing change in open source software ecosystems.
Help shape the evolution of open source software and work closely with Jim Herbsleb
Community Code Engagements: Summer of Code & Hackathons for Community Building in Scientific Software
Studies how coding events foster community and innovation in scientific software.
Join the movement to build stronger scientific software communities and work closely with Jim Herbsleb
Trust in Collaborative Automation in High Stakes Software Engineering Work: A Case Study at NASA
Investigates trust in AI tools for critical software engineering at NASA.
Research real-world AI challenges with Laura Dabbish
Missing Pieces: How Framing Uncertainty Impacts Longitudinal Trust in AI Decision Aids--A Gig Driver Case Study
Examines trust in AI-driven decision aids for gig drivers, focusing on income estimate presentations
Help design AI tools that empower gig workers with Laura Dabbish
Join Our Research Community
As a PhD student in Societal Computing, you’ll collaborate with leading faculty like Kathleen M. Carley, Laura Dabbish, Jim Herbsleb, Patrick Park, Norman Sadeh, and Bogdan Vasilescu to advance research in complex socio-technical systems. Contribute to cutting-edge projects, from analyzing social network dynamics to enhancing privacy and security, and shape the future of technology and society.
Funding and Support
All admitted PhD students in the Societal Computing program receive full funding, including tuition and a living stipend, through research assistantships, teaching assistantships, and fellowships. This support ensures you can focus on groundbreaking research in areas like social network dynamics and privacy.