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

aimingoo的专栏
aimingoo的专栏
宝玉的分享
宝玉的分享
J
Java Code Geeks
Martin Fowler
Martin Fowler
博客园 - Franky
I
InfoQ
Stack Overflow Blog
Stack Overflow Blog
Blog — PlanetScale
Blog — PlanetScale
S
SegmentFault 最新的问题
B
Blog
The Cloudflare Blog
F
Fortinet All Blogs
量子位
腾讯CDC
博客园 - 司徒正美
D
Docker
大猫的无限游戏
大猫的无限游戏
Microsoft Azure Blog
Microsoft Azure Blog
T
The Blog of Author Tim Ferriss
V
Visual Studio Blog
IT之家
IT之家
Last Week in AI
Last Week in AI
D
DataBreaches.Net
小众软件
小众软件

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
Socially-Aware Networking: A Survey
Feng Xia, Li Liu, Jie Li, Jianhua Ma, Athanasios V. Vasilakos · 2013-12-23 · via cs.SI updates on arXiv.org

The widespread proliferation of handheld devices enables mobile carriers to be connected at anytime and anywhere. Meanwhile, the mobility patterns of mobile devices strongly depend on the users' movements, which are closely related to their social relationships and behaviors. Consequently, today's mobile networks are becoming increasingly human centric. This leads to the emergence of a new field which we call socially-aware networking (SAN). One of the major features of SAN is that social awareness becomes indispensable information for the design of networking solutions. This emerging paradigm is applicable to various types of networks (e.g. opportunistic networks, mobile social networks, delay tolerant networks, ad hoc networks, etc) where the users have social relationships and interactions. By exploiting social properties of nodes, SAN can provide better networking support to innovative applications and services. In addition, it facilitates the convergence of human society and cyber physical systems. In this paper, for the first time, to the best of our knowledge, we present a survey of this emerging field. Basic concepts of SAN are introduced. We intend to generalize the widely-used social properties in this regard. The state-of-the-art research on SAN is reviewed with focus on three aspects: routing and forwarding, incentive mechanisms and data dissemination. Some important open issues with respect to mobile social sensing and learning, privacy, node selfishness and scalability are discussed.