BleacherBot: AI Agent as a Sports Co-Viewing Partner

Co-viewing, traditionally defined as watching content together in the same physical space, enhances emotional connections through shared experiences. With the rise of remote viewing during the COVID-19 pandemic, existing solutions, such as second-screen platforms and rule-based AI companions, struggle to facilitate meaningful social interactions. This study explores the potential of Large Language Models, which offer human-like interactions and personalization. Our formative study with ten participants revealed the importance of managing arousal levels, highlighting the need to balance between high- and low-arousal levels across different viewing contexts. Based on these insights, we developed ‘BleacherBot’, a sports co-viewing agent with distinct interaction styles that vary in arousal levels. Our main study with 27 participants demonstrated that matching users’ preferred arousal levels with the agent’s interaction style significantly enhanced their engagement and overall enjoyment. We propose design guidelines for AI co-viewing agents that consider their role as complements to human social interactions.