Can AI automatically analyze public opinion? A LLM agents-based agentic pipeline for timely public opinion analysis

• URL: http://arxiv.org/abs/2505.11401v1
• Date: Fri, 16 May 2025 16:09:28 GMT
• Title: Can AI automatically analyze public opinion? A LLM agents-based agentic pipeline for timely public opinion analysis
• Authors: Jing Liu, Xinxing Ren, Yanmeng Xu, Zekun Guo,
• Abstract summary: This study proposes and implements the first LLM agents based agentic pipeline for multi task public opinion analysis.<n>Unlike traditional methods, it offers an end-to-end, fully automated analytical workflow without requiring domain specific training data.<n>It enables timely, integrated public opinion analysis through a single natural language query.
• Score: 3.1894345568992346
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This study proposes and implements the first LLM agents based agentic pipeline for multi task public opinion analysis. Unlike traditional methods, it offers an end-to-end, fully automated analytical workflow without requiring domain specific training data, manual annotation, or local deployment. The pipeline integrates advanced LLM capabilities into a low-cost, user-friendly framework suitable for resource constrained environments. It enables timely, integrated public opinion analysis through a single natural language query, making it accessible to non-expert users. To validate its effectiveness, the pipeline was applied to a real world case study of the 2025 U.S. China tariff dispute, where it analyzed 1,572 Weibo posts and generated a structured, multi part analytical report. The results demonstrate some relationships between public opinion and governmental decision-making. These contributions represent a novel advancement in applying generative AI to public governance, bridging the gap between technical sophistication and practical usability in public opinion monitoring.

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