Bridget Smart

Bridget Smart is a Research Fellow at the Mathematical Institute, University of Oxford, within the Department of MATH. Her research interests include complex systems, network science, information theory, and computational social science, with a focus on modeling and characterizing uncertainty in real-world systems. She has contributed to studies on information flows in networks, bot-human interactions, and the dynamics of social media. Smart has held teaching roles at Oxford University and the University of Adelaide, covering courses in mathematics, data science, and statistics. She is supervised by Professor Renaud Lambiotte and Professor Doyne Farmer and collaborates with the Institute of New Economic Thinking Oxford (INET).

Bridget Smart is a researcher at the University of Oxford, focusing on the intersection of computational methods and social dynamics in information dissemination. Her work explores the role of bots and humans in shaping public discourse, particularly in politically charged contexts such as the Russia-Ukraine war. She also investigates information flow on platforms like Twitter, with an emphasis on how news spreads and is interpreted. Smart's research includes the development of algorithms for efficient data analysis, such as longest common substring calculation for entropy estimation in sequential data. Her studies often involve agent-based modeling to simulate prediction market manipulation and the behavior of complex systems. Her work contributes to understanding how information is processed and manipulated in digital environments.