Unpacking self-regulation and social interaction in “Study With Me” videos through large-scale analytics

Abstract

As social media platforms are increasingly used to facilitate informal learning, “Study With Me” (SWM) videos have garnered substantial popularity. Despite their widespread use, empirical research on these videos remains in its infancy. This study investigates the characteristics of SWM videos, providing a comprehensive understanding of their affordances for self-regulated learning and social interaction. Specifically, advanced machine learning techniques were applied to analyze 393 SWM videos and 164,611 associated comments on YouTube. A modified topic modeling approach identified emerging themes and patterns in the comment data, while sentiment analysis assessed emotional tone and examined how specific video features influenced users' self-regulation. The analysis revealed that comments primarily focused on SWM video features, self-regulation, and social interaction. Positive sentiment appeared in about half of the comments, praising elements such as ambient music and visual aesthetics for enhancing emotional engagement and motivation. Various features of SWM videos, such as lighting, music, and in-video text, support learners’ self-regulation across motivational, emotional, and social dimensions. This study highlights the potential of social media as a versatile educational tool and encourages stakeholders to leverage such platforms to expand and enrich learning opportunities.