- The Effects of Adversarial Agents on Social Networks
- Project Year:
2024
- REU Student (s):
Rhett Olson | University of Minnesota-Twin Cities MN
- Student 1 Institution:
University of Minnesota-Twin Cities
- Project Mentor:
Jie Gao
- Project Mentor Area:
Computer Science
- Project Abstract:
To make better decisions, agents often try to aggregate information from others. This phenomenon has been studied extensively through the lens of social networks. However, in real-world settings, one cannot always assume that others intend to make the best decision, or share their information honestly. Such agents act as adversaries for the task of social learning. This research investigates whether social networks can be used to aggregate information in a way that is robust against such adversaries. We present results on the robustness of two specific social networks: the Celebrity network and the Butterfly network. These results improve our understanding of how information can be aggregated effectively in social networks, both in networks with high-degree nodes and networks where all nodes have a constant degree.
