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cs.SI updates on arXiv.org

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? A Multi-Dimensional Study of Culture, Language, Scale, and Method Moltbook Moderation: Uncovering Hidden Intent Through Multi-Turn Dialogue Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks Predicting Channel Closures in the Lightning Network with Machine Learning Latent Causal Void: Explicit Missing-Context Reconstruction for Misinformation Detection Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence When Can Digital Personas Reliably Approximate Human Survey Findings? RAwR: Role-Aware Rewiring via Approximate Equitable Partition GravityGraphSAGE: Link Prediction in Directed Attributed Graphs Structure-Centric Graph Foundation Model via Geometric Bases Attention-based graph neural networks: a survey When AI Meets Science: Research Diversity, Interdisciplinarity, Visibility, and Retractions across Disciplines in a Global Surge Scalable inference of spatial regions and temporal signatures from time series Can LLMs Emulate Human Belief Dynamics? Predicting Post Virality with Temporal Cross-Attention over Trend Signals H3: A Healthcare Three-Hop Index for Physician Referral Network Prediction Dynamic Graph with Similarity-Aware Attention Graph Neural Network for Recommender Systems Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks Topological Neural Tangent Kernel Empowering Heterogeneous Graph Foundation Models via Decoupled Relation Alignment Aitchison Embeddings for Learning Compositional Graph Representations Social Bias in LLM-Generated Code: Benchmark and Mitigation Stable Behavior, Limited Variation: Persona Validity in LLM Agents for Urban Sentiment Perception The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs Emotion-Aware Clickbait Attack in Social Media DiRe-RAPIDS: Topology-faithful dimensionality reduction at scale Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface Shape of Memory: a Geometric Analysis of Machine Unlearning in Second-Order Optimizers Misinformation Span Detection in Videos via Audio Transcripts The CriticalSet problem: Identifying Critical Contributors in Bipartite Dependency Networks AI-Gram: When Visual Agents Interact in a Social Network XFlowMap: Cross-Scale Generalization and Mapping of Massive Origin-Destination Data When Graph Structure Becomes a Liability: A Critical Re-Evaluation of Graph Neural Networks for Bitcoin Fraud Detection under Temporal Distribution Shift Assessing Capabilities of Large Language Models in Social Media Analytics: A Multi-task Quest The Triadic Loop: A Framework for Negotiating Alignment in AI Co-hosted Livestreaming Optimal Exploration of New Products under Assortment Decisions Spectral Analysis of Fake News Propagation Polarization by Default: Auditing Recommendation Bias in LLM-Based Content Curation Graph self-supervised learning based on frequency corruption The Moltbook Observatory Archive: an incremental dataset of agent-only social network activity Connecting online criminal behavior with machine learning: Using authorship attribution to analyze and link potential online traffickers The Impact of AI-Generated Text on the Internet Network Effects and Agreement Drift in LLM Debates Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis PERCEIVE: A Benchmark for Personalized Emotion and Communication Behavior Understanding on Social Media Creator Incentives in Recommender Systems: A Cooperative Game-Theoretic Approach for Stable and Fair Collaboration in Multi-Agent Bandits Ollivier-Ricci Curvature of Riemannian Manifolds and Directed Graphs with Applications to Graph Neural Networks Structural Diversity Drives Disruptive Scientific Innovation SP-GCRL: Influence Maximization on Incomplete Social Graphs Beyond Individual Mimicry: Constructing Human-Like Social network with Graph-Augmented LLM Agents Real-World Challenges in Fake News Detection: Dealing with Posts by Cold Users Measuring the Semantic Structure and Evolution of Conspiracy Theories Inference Headroom Ratio: A Diagnostic and Control Framework for Inference Stability Under Constraint Counting Without Numbers and Finding Without Words WhatsApp Vaccine Discourse (WhaVax): An Expert-Annotated Dataset and Benchmark for Health Misinformation Detection When Annotators Agree but Labels Disagree: The Projection Problem in Stance Detection Representing Higher-Order Networks: A Survey of Graph-Based Frameworks XNote: Benchmarking Automated Community Notes Generation for Image-based Contextual Deception Can LLM Agents Simulate Dynamic Networks? 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
TruthBot: An Automated Conversational Tool for Intent Learning, Curated Information Presenting, and Fake News Alerting
Ankur Gupta, Yash Varun, Prarthana Das, Nithya Muttineni, Parth · 2021-02-01 · via cs.SI updates on arXiv.org

We present TruthBot, an all-in-one multilingual conversational chatbot designed for seeking truth (trustworthy and verified information) on specific topics. It helps users to obtain information specific to certain topics, fact-check information, and get recent news. The chatbot learns the intent of a query by training a deep neural network from the data of the previous intents and responds appropriately when it classifies the intent in one of the classes above. Each class is implemented as a separate module that uses either its own curated knowledge-base or searches the web to obtain the correct information. The topic of the chatbot is currently set to COVID-19. However, the bot can be easily customized to any topic-specific responses. Our experimental results show that each module performs significantly better than its closest competitor, which is verified both quantitatively and through several user-based surveys in multiple languages. TruthBot has been deployed in June 2020 and is currently running.

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