Network Analysis of Fake News Propagation on Social Media
Summer 2026:
Network Analysis of Fake News Propagation on Social Media: We are embedding our previously developed probability model for the propagation of fake news on social media into a network propagation framework. We seek to understand the conditions causing untruthful or highly biased news to “cascade” through the network, and the influence such content has on population beliefs. The work will involve experimental design, simulating the effect of policy interventions, and drawing conclusions.
Interested students should indicate in their application essay any relevant coursework. Programming proficiency is a necessary skill; background or interest in operations research preferred. This is applied research, so students should expect a fair number of computational tasks. However it is not just a coding project.
Student participation in this project is contingent on funding availability. The period of the research experience will be eight weeks, from May 18 - July 10 with federal holidays observed on May 26, June 19, and July 3.
This is a great opportunity for students who want to learn how to use mathematical models to inform public policy.