惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Google DeepMind News
Google DeepMind News
C
Check Point Blog
J
Java Code Geeks
腾讯CDC
Martin Fowler
Martin Fowler
MongoDB | Blog
MongoDB | Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
博客园 - 三生石上(FineUI控件)
Apple Machine Learning Research
Apple Machine Learning Research
大猫的无限游戏
大猫的无限游戏
Engineering at Meta
Engineering at Meta
罗磊的独立博客
Last Week in AI
Last Week in AI
B
Blog
IT之家
IT之家
S
SegmentFault 最新的问题
D
DataBreaches.Net
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
GbyAI
GbyAI
博客园 - 聂微东
U
Unit 42
有赞技术团队
有赞技术团队
Y
Y Combinator Blog
MyScale Blog
MyScale Blog

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
From the CDC to emerging infectious disease publics: The ...
Tawfiq Ammari, Anna Gutowska, Jacob Ziff, Casey Randazzo, Hariha · 2025-03-26 · via cs.SI updates on arXiv.org

This study examines how public discourse around COVID-19 unfolded on Twitter through the lens of crisis communication and digital publics. Analyzing over 275,000 tweets involving the CDC, we identify 16 distinct discourse clusters shaped by framing, sentiment, credibility, and network dynamics. We find that CDC messaging became a flashpoint for affective and ideological polarization, with users aligning along competing frames of science vs. freedom, and public health vs. political overreach. Most clusters formed echo chambers, while a few enabled cross cutting dialogue. Publics emerged not only around ideology but also around topical and emotional stakes, reflecting shifting concerns across different stages of the pandemic. While marginalized communities raised consistent equity concerns, these narratives struggled to reshape broader discourse. Our findings highlight the importance of long-term, adaptive engagement with diverse publics and propose design interventions such as multi-agent AI assistants, to support more inclusive communication throughout extended public health crises.