social-media-signals

Community

Turn social chatter into trade-ready signals.

Authorloanntc
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Social-media posts and community discussions contain noisy, high-volume sentiment that is hard to convert into consistent signals for sentiment-driven trading decisions.

Core Features & Use Cases

  • Multi-Platform Financial Intelligence: Collect and structure signals from Twitter/X, Telegram, Discord, and Reddit to track how attention and sentiment evolve across venues.
  • Sentiment Quantification & Discussion Buzz Metrics: Apply sentiment scoring (including finance-aware options) and compute buzz/anomaly indicators to detect shifts in fear/greed and retail momentum.
  • Trading-Factor Construction: Build aggregated sentiment factors, test information coefficient (IC/ICIR) against forward returns, and optionally orthogonalize sentiment vs traditional factors to reduce overlap.

Quick Start

Use the social-media-signals skill to aggregate sentiment across Twitter/X, Telegram, Discord, and Reddit for a specified ticker and timeframe, then produce a structured sentiment factor with buzz metrics suitable for trading strategy evaluation.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: social-media-signals
Download link: https://github.com/loanntc/Paave/archive/main.zip#social-media-signals

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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