Department of Computer Engineering

Social media platforms are frequently exploited for manipulation, leading to increased polarization and the spread of narratives with hidden agendas. This talk will present computational approaches to detect, analyze, and understand these phenomena. First, we will explore social media manipulation by examining Cross-Partisan Interactions (CPIs) on Twitter, analyzing the user characteristics, topics, and stances that define these dialogues. Next, the talk introduces NARRA-SCALE, a novel framework for mapping ideological positioning by integrating network analysis with narrative and stance detection. Finally, this methodology is extended to conduct ideological diagnostics at scale, quantifying the inherent biases across 33 major LLMs. The research aims to provide tools for identifying polarization hotspots, demonstrate the mechanics of social media manipulation and contribute to the development of responsible AI and healthier online ecosystems.