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

IT之家
IT之家
A
About on SuperTechFans
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
N
Netflix TechBlog - Medium
Microsoft Security Blog
Microsoft Security Blog
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
博客园 - 三生石上(FineUI控件)
博客园 - 聂微东
博客园 - Franky
D
Docker
Martin Fowler
Martin Fowler
Engineering at Meta
Engineering at Meta
The Cloudflare Blog
人人都是产品经理
人人都是产品经理
Last Week in AI
Last Week in AI
U
Unit 42
F
Fortinet All Blogs
H
Help Net Security
Blog — PlanetScale
Blog — PlanetScale
Microsoft Azure Blog
Microsoft Azure Blog
罗磊的独立博客
P
Proofpoint News Feed
月光博客
月光博客
G
Google Developers 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
Analyzing digital politics: Challenges and experiments in...
2019-03-14 · via cs.SI updates on arXiv.org

Social networks have become in the last decade central to political life. However, to those interested in analysing the communication strategies of parties and candidates at election time, the introduction of the Internet into the political sphere has proved a mixed blessing. Indeed, while retrieving, consulting, and archiving original documents pertaining to a specific campaign have become easier, faster, and achievable on a larger scale, thus opening up a promising El Dorado for research in this area, studying online campaigns has also inevitably introduced new technical, methodological and legal challenges which have turned out to be increasingly complex for academics in the humanities and social sciences to solve on their own.This paper therefore proposes to provide feedback on experience and experimental validation from a multidisciplinary project called POLIWEB devoted to the comparative analysis of political campaigns on social media in the run up to the 2014 elections to the European Parliament in France and in the United Kingdom. Together with observations from a humanities' perspective on issues related to such a project, this paper also presents experimental results concerning three of the data collection life cycle phases: collection, cleaning, and storage. The outcome is a data collection ready to be analysed for various purposes meant to address the political science topic under consideration.