Year: 2025
Type: article
Abstract: Amid rising concerns over moderation, algorithmic control, and platform governance on centralized social media, people are increasingly turning to decentralized alternatives like Mastodon to regain control over their feeds. This shift offers new opportunities to understand how people perceive and curate their feeds. We conducted a two-part study with 21 Mastodon users: first, interviews exploring how they perceive and manage their feeds; and second, a design probe study using BRAIDS.SOCIAL, a web-based feed curation prototype informed by the first part of our initial findings. We learned how seamful design can increase people's trust in algorithmic curation, and surfaced trade-offs people navigate between machine learning-based and rule-based filtering approaches. We also identify a core design tension in decentralized platforms: whether to support personalization through new applications or extensions layered atop existing ones.
DOI: 10.1145/3757688
Institution: Princeton University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4415259377