Agent skill · data analytics · aradotso
llm-intelligent-public-opinion-analytics
Deploy and use an LLM-powered public opinion analytics assistant that crawls 26 hot lists from 15 platforms, performs sentiment analysis, topic clustering, and multi-channel alerting
Why this skill is useful
Adds a complete LLM-powered public opinion analytics system with executable scripts for data crawling, sentiment analysis, and multi-channel alerting.
What it needs
Requires chromedriver, mysql, python installed locally. Requires openai account access. About 6k tokens when loaded. Last updated 2026-08-05. 5 stars on the source repository.
What this skill does
LLM-Based Intelligent Public Opinion Analytics Assistant Skill by ara.so — Data Skills collection. Overview This project is a comprehensive public opinion analytics platform that combines real-time data from 26 hot lists across 15 mainstream platforms (Weibo, Bilibili, Zhihu, Baidu, etc.) with large language model (LLM) analysis capabilities. It provides conversational query interfaces for hot searches, topic clustering, sentiment analysis, and multi-channel push notifications (WeChat, Email, Telegram). Key Capabilities: Real-time crawler cluster for 15+ platforms LLM-powered content analysis (including video content extraction) Natural language query interface Topic clustering and sentiment analysis Multi-channel alert system (Email, WeChat Work, Telegram) Keyboard shortcuts for crawler control Installation Prerequisites 1. Browser Driver Setup (Required for detail page scraping): 2. MySQL Database: 3. Python Environment: Database Initialization Reference the init.py file to create necessary tables: Configuration Environment Variables Create .env file in the project root: Crawler Settings Edit hotsearchcrawler/settings.py: Usage Starting the System Crawler Management Via Web Interface: Use keyboard shortcuts to start/stop crawlers View real-time crawling status Monitor data collection metrics Natural Language Queries Programmatic API Usage Push Notification Setup Analysis Report Generation Common Patterns Multi-Platform Data Aggregation Video Content Analysis Custom LLM Integration Scheduled Monitoring Troubleshooting Browser Driver Issues Database Connection Errors Crawler Rate Limiting LLM API Timeouts Memory Issues with Large Datasets Project Structure Reference Best Practices 1. Database Indexing: Ensure indexes on platform, crawltime, and title columns for fast queries 2. LLM Cost Management: Cache analysis results to avoid redundant API calls 3. Crawler Politeness: Respect platform rate limits and robots.txt 4. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aradotso/llm-intelligent-public-opinion-analytics