Self-moderation in the decentralized era: decoding blocking behavior on Bluesky
It addresses the challenge of balancing community safety and user autonomy in decentralized networks, which is critical for platform designers and researchers, though it is incremental as it applies existing analytical methods to a new context.
This study tackled the problem of understanding self-moderation in decentralized social networks by analyzing user blocking behavior on Bluesky, finding that the likelihood of a user being blocked is inferable from their online behavior and identifying specific behavioral features associated with increased blocking risk.
Moderation and blocking behavior, both closely related to the mitigation of abuse and misinformation on social platforms, are fundamental mechanisms for maintaining healthy online communities. However, while centralized platforms typically employ top-down moderation, decentralized networks rely on users to self-regulate through mechanisms like blocking actions to safeguard their online experience. Given the novelty of the decentralized paradigm, addressing self-moderation is critical for understanding how community safety and user autonomy can be effectively balanced. This study examines user blocking on Bluesky, a decentralized social networking platform, providing a comprehensive analysis of over three months of user activity through the lens of blocking behaviour. We define profiles based on 86 features that describe user activity, content characteristics, and network interactions, addressing two primary questions: (1) Is the likelihood of a user being blocked inferable from their online behavior? and (2) What behavioral features are associated with an increased likelihood of being blocked? Our findings offer valuable insights and contribute with a robust analytical framework to advance research in moderation on decentralized social networks.