Social Media Feedback Dynamics: The Influence of Community and Technology on Content Creators

This study explores how content creators interpret and handle feedback on social media platforms. The feedback, categorised as either community-induced or technology-induced, parallels formative and summative assessments in education. While community-induced feedback evolves through likes, comments, and direct messages, technology-induced feedback reflects performance metrics governed by algorithms. Understanding the impact of these feedback types on individuals and society, especially as digital platforms become more prevalent, is critical. Exploring content creators’ viewpoints on various types of feedback, we conducted in-depth interviews with 15 individuals across platforms like YouTube, Twitch, Instagram, and TikTok, employing interpretive qualitative methods and grounded theory methodology. We propose a model illustrating community-induced and technology-induced feedback sequences, presenting the inner workings of these feedback loops. Our research reveals content creators’ strategies for managing negative community engagement, including comment deletion and user blocking. Additionally, our findings shed light on their efforts to distinguish and navigate themselves amidst technology-induced feedback.