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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
Convergence Behaviour of Bystanders: An Analysis of 2016 Munich Shooting Twitter Crisis Communication
Deborah Bunker, Milad Mirbabaie, Stefan Stieglitz · 2020-04-18 · via cs.SI updates on arXiv.org

While convergence behaviour archetypes can explain behaviour of individuals who actively converge on and participate in crises, less is known about individuals who converge on an event and choose to remain passive i.e. "bystanders". Bystanders are important, because of their proximity to an event and their function as an "eye-witness". To investigate the role of bystanders in crisis communications we analysed Twitter communication generated from the 2016 Munich Shooting event. Our findings revealed the impassive convergence behaviour archetype could influence an event as a passive and rational "eye-witness", by gathering and sharing information close to where the event is occurring.

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