用AI分析去中心化社交平台情绪与叙事，低成本可扩展。
CognitiveSky: Scalable Sentiment and Narrative Analysis for Decentralized Social Media
- 通过API接入Bluesky数据，用Transformer模型标注内容
- 生成结构化输出，实时可视化情绪与话题演变趋势
- 开源免费，适合研究心理、谣言或公共舆情的学者
去中心化社交平台的兴起为公共话语的实时分析带来新机遇与挑战。本研究提出CognitiveSky，一个开源且可扩展的框架，用于Bluesky（一种联邦制的Twitter/X替代平台）上的情感、情绪与叙事分析。通过Bluesky的API接入数据，CognitiveSky利用基于Transformer的模型对大规模用户生成内容进行标注，并输出结构化可分析的结果。这些结果驱动动态仪表板，可视化情绪、活跃度与对话主题的演化模式。整个系统完全基于免费层级基础设施构建，实现低运营成本与高可访问性。尽管以心理健康话题为例，其模块化设计支持在虚假信息检测、危机响应与公民情绪分析等多领域应用。CognitiveSky通过连接大语言模型与去中心化网络，为数字生态转型期的计算社会科学提供透明、可扩展的工具。
原文摘要 · Abstract (English)
The emergence of decentralized social media platforms presents new opportunities and challenges for real-time analysis of public discourse. This study introduces CognitiveSky, an open-source and scalable framework designed for sentiment, emotion, and narrative analysis on Bluesky, a federated Twitter or X.com alternative. By ingesting data through Bluesky's Application Programming Interface (API), CognitiveSky applies transformer-based models to annotate large-scale user-generated content and produces structured and analyzable outputs. These summaries drive a dynamic dashboard that visualizes evolving patterns in emotion, activity, and conversation topics. Built entirely on free-tier infrastructure, CognitiveSky achieves both low operational cost and high accessibility. While demonstrated here for monitoring mental health discourse, its modular design enables applications across domains such as disinformation detection, crisis response, and civic sentiment analysis. By bridging large language models with decentralized networks, CognitiveSky offers a transparent, extensible tool for computational social science in an era of shifting digital ecosystems.
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