Overview: Developed a framework aimed at analyzing the flow of information within social networks. This involved the use of generative agents to simulate social interactions, employing a modified Breadth-First Search (BFS) algorithm to structure these interactions efficiently. A scoring mechanism was designed to evaluate the dynamics of information propagation within the network, providing insights into how information spreads in social settings powered by artificial agents.
Overview: Conducted a detailed investigation into how various graph models and node properties influence the robustness of networks. This project focused on understanding the underlying dynamics that contribute to network stability and efficiency.