Professor Amir Leshem's research in information processing for social networks and opinion dynamics focuses on understanding how information and influence propagate through complex social systems. By integrating tools from signal processing, game theory, and graph-based modeling, his work explores how opinions form, evolve, and polarize within networks, and how malicious actors can manipulate public discourse through coordinated campaigns. His research aims to develop algorithms for detecting misinformation, modeling trust and influence, and designing resilient information ecosystems that support truthful and diverse communication. These insights have broad applications in combating fake news, analyzing public sentiment, and safeguarding democratic processes in the digital age.