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

The GitHub Blog
The GitHub Blog
I
InfoQ
U
Unit 42
WordPress大学
WordPress大学
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
Apple Machine Learning Research
Apple Machine Learning Research
J
Java Code Geeks
月光博客
月光博客
D
Docker
Stack Overflow Blog
Stack Overflow Blog
D
DataBreaches.Net
阮一峰的网络日志
阮一峰的网络日志
Blog — PlanetScale
Blog — PlanetScale
V
Visual Studio Blog
博客园 - 聂微东
A
About on SuperTechFans
腾讯CDC
Jina AI
Jina AI
Microsoft Azure Blog
Microsoft Azure Blog
GbyAI
GbyAI
博客园 - 【当耐特】
罗磊的独立博客
博客园 - 三生石上(FineUI控件)
M
MIT News - Artificial intelligence

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
Exploring the Public Reaction to COVID-19 News on Social ...
Luciana Oliveira, Arminda Sequeira, Adriana Oliveira, Paulino Si · 2021-02-16 · via cs.SI updates on arXiv.org

The outburst and proliferation of the COVID-19 pandemic, together with the subsequent social distancing measures, have raised massive challenges in almost all domains of public and private life around the globe. The stay-at-home movement has pushed the news audiences into social networks, which, in turn, has become the most prolific field for receiving and sharing news updates, as well as for public expression of opinions, concerns and feelings about the pandemic. Public opinion is a critical aspect in analysing how the information and events impact peoples lives, and research has shown that social media data may be promising in understanding how people respond to health risks and social crisis, which are the feelings they tend to share and how they are adapting to unforeseen circumstances that threaten almost all societal spheres. This paper presents results from a social media analysis of 61532 news headlines posted by the major daily news outlet in Portugal, Sic Noticias, on Facebook, from January to December 2020, focusing on the issues attention cycle and audiences emotional response to the COVID news outburst. This work adds to the emergent body of studies examining public response to the coronavirus pandemic on social media data.