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Navigating Decentralized Online Social Networks: An Overview of Technical and Societal Challenges in Architectural Choices
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Navigating Decentralized Online Social Networks: An Overview of Technical and Societal Challenges in Architectural Choices
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Decentralized online social networks have evolved from experimental stages to operating at unprecedented scale, with broader adoption and more active use than ever before. Platforms like Mastodon, Bluesky, Hive, and Nostr have seen notable growth, particularly following the wave of user migration after Twitter's acquisition in October 2022. As new platforms build upon earlier decentralization architectures and explore novel configurations, it becomes increasingly important to understand how these foundations shape both the direction and limitations of decentralization. Prior literature primarily focuses on specific architectures, resulting in fragmented views that overlook how different social networks encounter similar challenges and complement one another. This paper fills that gap by presenting a comprehensive view of the current decentralized online social network landscape. We examine four major architectures: federated, peer-to-peer, blockchain, and hybrid, tracing their evolution and evaluating how they support core social networking functions. By linking these architectural aspects to real-world cases, our work provides a foundation for understanding the societal implications of decentralized social platforms.
Forward citations
Cited by 3 Pith papers
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The Activist's Guide to the Decentralized Social Universe: A Framework for Exploring How Decentralized Social Networks Can Support Collective Action
A conceptual framework is introduced that links activist needs to decentralized social network features and is applied to compare Mastodon and Bluesky plus example communities.
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The Activist's Guide to the Decentralized Social Universe: A Framework for Exploring How Decentralized Social Networks Can Support Collective Action
A framework is introduced that links activist needs (minimal overhead, community building, safety, sustainability) to DSN affordances and is applied to compare Mastodon and Bluesky plus example communities.
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Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence
The authors introduce a validation framework showing LLMs can pull causal links from disaster social media but require checks against post-event evidence to avoid relying on model priors.
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