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.
boyd and Nicole B
7 Pith papers cite this work, alongside 114 external citations. Polarity classification is still indexing.
7
Pith papers citing it
114
external citations · external index
representative citing papers
Moa is an anonymous social platform for PhD students that uses consent boundaries—per-post audience filters based on shared identity, experience, or affiliation—to facilitate sensitive conversations about advising relationships.
Proposes a social norms framework for youth social media design to overcome pluralistic ignorance and enable independent platforms focused on trusted connections.
An ablation study on 252 datasets finds that adding table schemas to LLM prompts consistently degrades narrative quality of generated descriptions compared to titles alone.
Reddit communities can be predicted to become hateful or dangerous months in advance using machine learning on changes in user base and discourse topics.
The dissertation proposes three methods to counter misattunements in youth social media design and develop youth-grounded criteria for supportive platforms.
Reflections on how uncritical acceptance of LLM answers violates Grice's Maxim of Quality and Lemoine's Maxim of Innocence while flawed detection tests risk mislabeling human work as AI-generated.
citing papers explorer
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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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Enabling Sensitive Conversations with Consent Boundaries: Moa, a Platform for Discussing PhD Advising Relationships
Moa is an anonymous social platform for PhD students that uses consent boundaries—per-post audience filters based on shared identity, experience, or affiliation—to facilitate sensitive conversations about advising relationships.
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A Social Norms Approach to Youth Social Media Design
Proposes a social norms framework for youth social media design to overcome pluralistic ignorance and enable independent platforms focused on trusted connections.
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Less Is More? When Dataset Context Hurts LLM-Generated Dataset Descriptions
An ablation study on 252 datasets finds that adding table schemas to LLM prompts consistently degrades narrative quality of generated descriptions compared to titles alone.
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To Act or React: Investigating Proactive Strategies For Online Community Moderation
Reddit communities can be predicted to become hateful or dangerous months in advance using machine learning on changes in user base and discourse topics.
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Problem Space Attunement in Youth Social Media Design
The dissertation proposes three methods to counter misattunements in youth social media design and develop youth-grounded criteria for supportive platforms.
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Epistemic reflections on AI answering our questions: overwatch, erudite, logician, interlocutor
Reflections on how uncritical acceptance of LLM answers violates Grice's Maxim of Quality and Lemoine's Maxim of Innocence while flawed detection tests risk mislabeling human work as AI-generated.