This study aims to analyze the structure of non-face-to-face actor performance in the context of digital transformation and to explore how actor performance is organized and regulated within a real-time platform-based environment. To this end, the stu...
This study aims to analyze the structure of non-face-to-face actor performance in the context of digital transformation and to explore how actor performance is organized and regulated within a real-time platform-based environment. To this end, the study examined the relationships among the major components of performance through the real-time interaction structure formed within a SOOP-based one-person media environment. Particular attention was given not to performance outcomes themselves, but to the structural relationships that emerge through the process by which performance is formed and organized.
The findings indicate that actor performance in non-face-to-face environments extends beyond the dimension of individual expression and is organized within a real-time interaction structure in which actors, coaches, viewers, and the platform as a technological mediator are simultaneously interconnected. In particular, coaching feedback, audience responses, and technological signals from the platform continuously intervene in the performance process and function as conditions that shape and regulate actors’ behaviors and responses. Furthermore, the elements of Action (K), Emotion and Sensation (L), and Interaction (S) were found to interact dynamically, being continuously reconfigured according to performance situations and relational responses rather than operating in a fixed sequence.
These findings suggest that the digital environment is not merely a technologically mediated space but a performance structure in which relational interactions are connected in real time, collectively organizing and shaping performance. By integratively analyzing the relationships among performance, response, and formation in non-face-to-face acting practice, this study proposes a performance model based on real-time interaction among actors, coaches, and viewers. Furthermore, it provides an analytical framework for understanding and explaining the structural operating mechanisms of non-face-to-face actor performance within rapidly changing digital environments and seeks to establish a foundation for future research on non-face-to-face actor training and real-time performance environments.