Social media platforms use algorithms to personalize user experiences, thereby revolutionizing how people consume information and connect with each other. Yet, the academic understanding of how users make sense of these algorithms is limited. However, this is relevant as algorithm sensemaking affects user behavior. Through in-depth, semi-structured interviews and building on prior work on media folk theories, this study investigates how Instagram users understand the platform’s algorithm, uncovering a new folk theory: Algorithms as being controllable, with users believing their actions shape algorithmic outcomes. However, deeper exploration reveals a lack of awareness about the extent of algorithmic influence on their behavior. By contextualizing and expanding algorithmic folk theories for social media, this study advances theoretical insights into the relationship between algorithm sensemaking, folk theories and user behavior. Furthermore, next steps of the ongoing research project and directions for future research are discussed.