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

G
Google Developers Blog
博客园 - 聂微东
J
Java Code Geeks
Engineering at Meta
Engineering at Meta
Jina AI
Jina AI
D
Docker
B
Blog
S
SegmentFault 最新的问题
宝玉的分享
宝玉的分享
D
DataBreaches.Net
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Y
Y Combinator Blog
N
Netflix TechBlog - Medium
月光博客
月光博客
F
Fortinet All Blogs
爱范儿
爱范儿
H
Help Net Security
腾讯CDC
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
WordPress大学
WordPress大学
The Cloudflare Blog
有赞技术团队
有赞技术团队
T
Tailwind CSS Blog
U
Unit 42

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
Berlin: A Quantitative View of the Structure of Instituti...
Aliakbar Akbaritabar · 2020-08-19 · via cs.SI updates on arXiv.org

This paper examines the structure of scientific collaborations in a large European metropolitan area. It aims to identify strategic coalitions among organizations in Berlin as a specific case with high institutional and sectoral diversity. By adopting a global, regional and organization based approach we provide a quantitative, exploratory and macro view of this diversity. We use publications data with at least one organization located in Berlin from 1996-2017. We further investigate four members of the Berlin University Alliance (BUA) through their self-represented research profiles comparing it with empirical results of OECD disciplines. Using a bipartite network modeling framework, we are able to move beyond the uncontested trend towards team science and increasing internationalization. Our results show that BUA members shape the structure of scientific collaborations in the region. However, they are not collaborating cohesively in all disciplines. Larger divides exist in some disciplines e.g., Agricultural Sciences and Humanities. Only Medical and Health Sciences have cohesive intraregional collaborations which signals the success of regional cooperation established in 2003. We explain possible underlying factors shaping the observed trends and sectoral and intra-regional groupings. A major methodological contribution of this paper is evaluating coverage and accuracy of different organization name disambiguation techniques.