Master the application of computational methods to understand communication phenomena at the individual, group, and societal levels of analysis...
Scholars working in the exciting new field of Computational Social Science take advantage of computational tools to answer fundamental questions about human interactions, communications, and behaviors. The digital revolution not only changes how we communicate, but also how we can understand and study communication. Human beings are leaving massive digital footprints. Computers can discover patterns that were previously invisible, and artificial virtual worlds enable us to explore the most daring visions of our future. The field of Communication is at the forefront of these new methodologies, first and foremost because most of the online behavior footprints provide massive evidence of communication processes (‘big data’). This provides unprecedented opportunities to deepen our understanding of what communication is and what we can do about it, be it for individuals or societies. Computational approaches may include big data analytics, computer simulations, social network analysis, text mining, machine learning, large-scale experiments, cognitive modeling, time series analysis, and data visualization.
Computational social science is not about reworking old questions with newer methods and newer jargon. It is about a balanced education in social theories and computational methods that empowers you to be creative and ask entirely new kinds of questions about human sociality. It will enable Communication Scientists to discover previously unknown aspects of communication and information processes and their impact on individuals and society.
UC Davis is equidistant between Silicon Valley, Sonoma County, and California’s beautiful Sierra Nevada mountains. Few institutions with the resources of the University of California do so much to encourage the interdisciplinary contacts behind a successful education in Computational Social Science. At Davis, you will have opportunities to engage with the Complex Systems Center, the Social and Political Networks group, the Center for Mind and Brain, the new Data Science Initiative, and faculty in each of the behavioral sciences.
Our faculty brings to the study of Communication backgrounds in economics, sociology, political science, and psychology, as well as computer science, information science, cognitive science, and network science.
Communication Faculty: Seth Frey, Martin Hilbert, Richard Huskey, Magdalena Wojcieszak, Cuihua (Cindy) Shen, Jingwen Zhang. Distinguished Professor Emeritus George Barnett continues to work with graduate students in the program.
Affiliated Faculty: Xiaoling Shu (Sociology)
Ongoing Research Programs
- Exploring how people create and maintain social and collaborative networks in massively multiplayer online games and peer production communities
- Investigating the mechanisms of communication campaign effects using agent-based simulations
- Understanding the role of social algorithms and artificial intelligence in society
- Using persuasive messages to increase the effectiveness of mobile games targeting depression.
- Designing and testing social network-based mobile apps to promote physical activity
- Developing health information technologies to harness the wisdom of crowds to improve diagnosis
- Understanding team dynamics and proposing more efficient ways to collaborate
- Modeling the design and evolution of effective online communities
CMN 212: Web Science Research Methods
CMN 213: Simulation Methods in Communication Research
CMN 214: Analysis of Communication Networks
CMN 233: Persuasive Technologies for Health
CMN 251: Digital Technology and Social Change
CMN 255: Social Media
CMN 256: Communication Perspectives on Video Game
CMN 270: Diffusion of Innovations
"What can I do with this?"
Computational communication research students are in high demand in academia, industry, or public sectors. Example career opportunities include tenure-track faculty, data scientist, user experience researcher, social media marketing manager, policy analyst, among others.
“Using computational social science, I've learned how to ask theory-driven research questions and apply rigorous methods to test social theories on large-scale or digital trace data. These skills have enabled me to study the social networks and teams within many different online communities, such as video game players or Wikipedia editors. Through my graduate education at UC Davis, I am fortunate that I have had the opportunities to present my research internationally, collaborate with people across disciplines, and intern at Facebook multiple times.”
Class of 2018