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
F
Fortinet All Blogs
Microsoft Azure Blog
Microsoft Azure Blog
腾讯CDC
Vercel News
Vercel News
Recent Announcements
Recent Announcements
博客园 - Franky
小众软件
小众软件
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
The Cloudflare Blog
宝玉的分享
宝玉的分享
I
InfoQ
博客园 - 聂微东
Jina AI
Jina AI
J
Java Code Geeks
V
V2EX
U
Unit 42
Stack Overflow Blog
Stack Overflow Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
阮一峰的网络日志
阮一峰的网络日志
L
LangChain Blog
T
The Blog of Author Tim Ferriss
量子位

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
On the Relation Between Opinion Change and Information Co...
Flavio Petruzzellis, Corrado Monti, Gianmarco De Francisci Moral · 2022-07-25 · via cs.SI updates on arXiv.org

While much attention has been devoted to the causes of opinion change, little is known about its consequences. Our study sheds a light on the relationship between one user's opinion change episode and subsequent behavioral change on an online social media, Reddit. In particular, we look at r/ChangeMyView, an online community dedicated to debating one's own opinions. Interestingly, this forum adopts a well-codified schema for explicitly self-reporting opinion change. Starting from this ground truth, we analyze changes in future online information consumption behavior that arise after a self-reported opinion change on sociopolitical topics; and in particular, operationalized in this work as the participation to sociopolitical subreddits. Such participation profile is important as it represents one's information diet, and is a reliable proxy for, e.g., political affiliation or health choices. We find that people who report an opinion change are significantly more likely to change their future participation in a specific subset of online communities. We characterize which communities are more likely to be abandoned after opinion change, and find a significant association (r=0.46) between propaganda-like language used in a community and the increase in chances of leaving it. We find comparable results (r=0.39) for the opposite direction, i.e., joining a community. This finding suggests how propagandistic communities act as a first gateway to internalize a shift in one's sociopolitical opinion. Finally, we show that the textual content of the discussion associated with opinion change is indicative of which communities are going to be subject to a participation change. In fact, a predictive model based only on the opinion change post is able to pinpoint these communities with an AP@5 of 0.20, similar to what can be reached by using all the past history of participation in communities.