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Hiding in Plain Sight: Finding MAHA on Reddit Prism: Structural Symmetry Scanning via Duality-Constrained Laplacian Projection MV-Gate: Insider Threat Detection via Multi-View Behavioral Statistics and Semantic Modeling Algorithmic Cultivation: How Social Media Feeds Shape User Language Universal Dynamics of Punctuated Progress AI-Mediated Communication Can Steer Collective Opinion CitePrism: Human-in-the-Loop AI for Citation Auditing and Editorial Integrity Explainable Detection of Depression Status Shifts from User Digital Traces Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles Humanwashing -- It Should Leave You Feeling Dirty When Do LLMs Generate Realistic Social Networks? 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A Case Study on Email Networks with Phishing Synthesis Form Without Function: Agent Social Behavior in the Moltbook Network Hijacking online reviews: sparse manipulation and behavioral buffering in popularity-biased rating systems Integration of Deep Reinforcement Learning and Agent-based Simulation to Explore Strategies Counteracting Information Disorder Who Shapes Brazil's Vaccine Debate? Semi-Supervised Modeling of Stance and Polarization in YouTube's Media Ecosystem Geodesic Semantic Search: Cartographic Navigation of Citation Graphs with Learned Local Riemannian Maps PACIFIER: Pacing Opinion Depolarization via a Unified Graph Learning Framework AI Agents Alone Are Not (Yet) Sufficient for Social Simulation Emergent Social Structures in Autonomous AI Agent Networks: A Metadata Analysis of 626 Agents on the Pilot Protocol What's Left Unsaid? Detecting and Correcting Misleading Omissions in Multimodal News Previews Social Story Frames: Contextual Reasoning about Narrative Intent and Reception Learning Multimodal Embeddings for Traffic Accident Prediction and Causal Estimation Context-Aware Detection and Victim-Centered Response Generation for Online Harassment in Private Messaging Beyond Leakage and Complexity: Towards Realistic and Efficient Information Cascade Prediction VERA-MH Concept Paper Beyond the Crowd: LLM-Augmented Community Notes for Governing Health Misinformation Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detection Digital Voices of Survival: From Social Media Disclosures to Support Provisions for Domestic Violence Victims Anti-establishment sentiment on TikTok: Implications for understanding influence(rs) and expertise on social media LLM Agents Are the Antidote to Walled Gardens Fast Geometric Embedding for Node Influence Maximization GARG-AML against Smurfing: A Scalable and Interpretable Graph-Based Framework for Anti-Money Laundering Unsupervised Learning of Local Updates for Maximum Independent Set in Dynamic Graphs Human-AI Governance (HAIG): A Trust-Utility Approach Patients Speak, AI Listens: LLM-based Analysis of Online Reviews Uncovers Key Drivers for Urgent Care Satisfaction Leveraging graph neural networks and mobility data for COVID-19 forecasting Opinion de-polarization in social networks with GNNs Leveraging Ensemble-Based Semi-Supervised Learning for Illicit Account Detection in Ethereum DeFi Transactions Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews
Data Trading with a Monopoly Social Network: Outcomes are Mostly Privacy Welfare Damaging
Ranjan Pal, Junhui Li, Yixuan Wang, Mingyan Liu, Swades De, Jon · 2020-12-16 · via cs.SI updates on arXiv.org

This paper argues that data of strategic individuals with heterogeneous privacy valuations in a distributed online social network (e.g., Facebook) will be under-priced, if traded in a monopoly buyer setting, and will lead to diminishing utilitarian welfare. This result, for a certain family of online community data trading problems, is in stark contrast to a popular information economics intuition that increased amounts of end-user data signals in a data market improves its efficiency. Our proposed theory paves the way for a future (counter-intuitive) analysis of data trading oligopoly markets for online social networks (OSNs).

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