Andreea Musulan

Supervised by: Jean-François Godbout
Université de Montréal

In Defense of Electoral Integrity: Detecting Inauthentic Activity

As inauthentic communication has become an increasingly challenging problem, my research project aims to produce insights into its evolution and detection. Using cutting edge machine learning, network, and temporal based approaches to analyzing cross-platform communication, and collaborating with a team of computer and political scientists at the Complex Data Lab, I will contribute to the development of techniques and methods for the detection of coordinated online activity. My goal is to help develop tools for policymakers and social media platforms that can help defend electoral integrity in democracies like Canada.