Modeling the Propagation of Fake News in Social Networks

Spring 2025:

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 finalizing the existing code base to run simulations through the network, analyzing data, 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.