Erin A Heerey, Samantha M Jones, Jeremias Campos, Amanda Friesen
The study of natural social behavior is a frontier discipline in psychology. Although such work is highly necessary for advancing and refining theories of social behavior, social cognition, evolutionary psychology, relationships, and more, researchers rarely commit to such intensive research designs due to the anticipated effort involved. In particular, to understand social behavior as it naturally unfolds, scientists must be able to collect and handle a high volume of rich social data efficiently, effectively, and reproducibly. Moreover, because social behavior is highly individualistic and context dependent, it is critical to capture variation in people's natural social behavior across multiple interaction partners. Here, we focus on "round-robin" research designs. Significant issues can arise in the administration of such designs, disincentivizing the collection of naturalistic round-robin social data. These include issues associated with participant nonattendance, experimenter error, the minimization of demand characteristics, and data management. Here, we provide a tutorial based on a recent study, with customizable resources designed to mitigate the inherent challenges associated with this type of research, including the semiautomation of in-person data collection and the automation of data management. (PsycInfo Database Record (c) 2026 APA, all rights reserved).