Studying a Multi-Agent Public-Opinion Analysis System

Overview

An evaluation of a mature open-source multi-agent public-opinion analysis system that monitors dozens of social platforms, mines large comment volumes, and produces analyst-style research reports. Studied as reference architecture for agent collaboration and analytics pipelines, not original studio authorship.

Why It Exists

We examined this OSS project (nearly 1,000 upstream commits) to learn how a production-grade, “ask-like-chatting” analytics agent is decomposed: how multiple specialized agents collaborate, how fine-tuned and statistical models sit alongside LLMs, and how raw social data becomes a finished report.

What We Built

This is an evaluation clone, framed honestly as R&D. The system is a pure-Python modular platform with discrete engines, ForumEngine, InsightEngine, MediaEngine, QueryEngine, ReportEngine, MindSpider (crawler), and a SentimentAnalysisModel, wired together through a Flask + SocketIO app with Streamlit report views and Docker deployment. We studied its “forum” debate mechanism (multiple agents with distinct toolsets debating under a moderator model), its multimodal handling of short-video and search-card content, and its public/private data fusion design.

Technologies & Approach

Python throughout: Flask, Flask-SocketIO, and Streamlit for the app and dashboards; OpenAI-compatible LLM interfaces plus Tavily search; pandas/numpy for data; fine-tuned sentiment models as middleware. The architecture’s value is the multi-engine separation and the agent-debate collaboration pattern.

Outcome / Impact

Provided a concrete reference for multi-agent collaboration, composite LLM-plus-statistical-model pipelines, and end-to-end report automation, directly transferable to our own analytics and agent work.

Capabilities Demonstrated

• Reading and assessing a large multi-agent codebase as architecture research
• Understanding agent-debate / “forum” collaboration patterns
• Sentiment analysis and public-opinion analytics pipelines
• Multimodal content extraction and automated HTML/MD/PDF report generation