Beyond Community Notes: A Framework for Understanding and Building Crowdsourced Context Systems for Social Media
Travis Lloyd, Tung Nguyen, Karen Levy, Mor Naaman
Abstract
Social media platforms are increasingly adopting features that display crowdsourced context alongside posts, a technique pioneered by X's Community Notes. These systems-which we term Crowdsourced Context Systems (CCS)-have the potential to reshape the information ecosystem as major platforms embrace them as alternatives to professional fact-checking. To understand the features and implications of these systems, we conduct a systematic literature review of existing CCS research (n=56) and analyze real-world CCS implementations. Based on our analysis, we develop a framework with two components. First, we present a theoretical model to conceptualize and define CCS. Second, we identify a design space encompassing six aspects: participation, inputs, curation, presentation, platform treatment, and transparency. We also surface normative implications of different CCS design and implementation choices. Our work integrates theoretical, design, and ethical perspectives to establish a foundation for future human-centered research on Crowdsourced Context Systems.
• Human-centered computing → Collaborative and social computing systems and tools; Empirical studies in collaborative and social computing.
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