sentiment-analysis

Analyze market sentiment using Python with Fear & Greed Index and social media data.

Updated May 25, 2026

Search Tags:#sentiment analysis #investment analysis #trading strategies #market sentiment #market indicators

Ready to run

npx skills add https://github.com/NigarumOvum/AutoTrading --skill sentiment-analysis-nigarumovum

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: sentiment-analysis
Source: https://github.com/NigarumOvum/AutoTrading/tree/main/Vibe-Trading/agent/src/skills/sentiment-analysis
Command: npx skills add https://github.com/NigarumOvum/AutoTrading --skill sentiment-analysis-nigarumovum

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scikit-learn, requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill quantifies market sentiment by converting subjective "fear and greed" into measurable indicators, helping users make informed investment decisions.

Core Features & Use Cases

Comprehensive Sentiment Analysis: Includes indicators like Fear & Greed Index, Put-Call Ratio, Margin Trading Signals, Northbound Funds Signals, and Social Media Sentiment Analysis.
Real-time Data Integration: Combines real-time market data with social media sentiment for a holistic view.
Use Case: Utilize this Skill to get a quick overview of market sentiment and adjust your investment strategy accordingly.

Quick Start

Analyze the current market sentiment by using the sentiment-analysis skill with the 'analyze' command.

Frequently Asked Questions about sentiment-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I quantify market sentiment for investment analysis?▼

This Skill quantifies market sentiment by converting subjective fear and greed into measurable indicators using Python. It applies machine learning models to market indicators and social media APIs for investment analysis.

What market indicators are used for real-time sentiment analysis?▼

Market sentiment analysis utilizes the Fear & Greed Index, Put-Call Ratio, Margin Trading Signals, Northbound Funds Signals, and Social Media Sentiment Analysis to provide a holistic view of real-time market conditions.

Do I need machine learning models to analyze market sentiment?▼

Yes, applying machine learning models is required to perform this sentiment analysis. The Skill relies on scikit-learn to process real-time market data and social media APIs to generate measurable sentiment indicators.

Can I use pandas and numpy for trading strategy sentiment signals?▼

Yes, you can use pandas and numpy to process market data and calculate sentiment signals for trading strategies. This Skill relies on these dependencies to process market indicators and output quantifiable sentiment metrics.

How do I analyze current market sentiment using Python?▼

You analyze current market sentiment by executing the 'analyze' command. This processes real-time market data and social media sentiment to help adjust your investment strategy accordingly.

What are the limitations of social media sentiment analysis for risk management?▼

Social media sentiment analysis for risk management requires continuous access to social media APIs and real-time market data sources. A limitation is its dependency on external API availability to maintain accurate sentiment signals.