UC San Diego

Although social media is often optimized for broadcasting visual information, studies of political social media have primarily focused on textual content. Concerns about synthetic images and influence operations have only widened our knowledge gap. This dissertation, comprising four papers, examines the supply of vision-based misinformation generated by autocratic actors, the demand for visual content in democracies across demographic groups, and the extent to which images can shape political behaviors, such as credibility perceptions toward news articles. Additionally, I investigate how information control in autocracies loses its effectiveness during crises. To answer these questions, I combine large-scale digital trace data, open-source pretrained models for computer vision and natural language processing, and causal inference methods. Overall, my work offers data-driven insights into the intersection of visual media, political communication, and information control.