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JacobHsu
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social-media-intelligence

Extract and standardize sentiment data from Twitter, Telegram, Discord, and Reddit.

Updated Apr 9, 2026
Search Tags:#twitter#reddit#trading#social-media#sentiment#data-collection#quant-strategy
One-click install
npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill social-media-intelligence-jacobhsu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: social-media-intelligence
Source: https://github.com/JacobHsu/vibe-trading-agent/tree/main/agent/src/skills/social-media-intelligence
Command: npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill social-media-intelligence-jacobhsu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Traders waste time manually monitoring Twitter/X, Telegram, Discord, and Reddit for sentiment shifts, missing key signals or reacting too late. This Skill centralizes guidance on collecting, scoring, and interpreting social chatter so you can spot actionable alpha without chasing each platform individually.

Core Features & Use Cases

  • Cross-platform ingestion: Offers tooling recipes for Twitter API/ntscraper, Telegram Telethon, Discord bots, and Reddit PRAW so you can harvest messages, engagement, and metadata with compliance-aware practices.
  • Quantified sentiment: Presents weighted scoring strategies (VADER, FinBERT, LLMs) plus buzz, fear-greed, and weighted-author methodologies to translate chatter into robust factors and reversal signals.
  • Use Case: Monitor a ticker around earnings, aggregate discussion volume and sentiment across platforms, and feed the resulting factor into your backtest to measure IC/ICIR impact before trading.

Quick Start

Ask the agent to scan Twitter, Telegram, Discord, and Reddit for a ticker, quantify the sentiment imbalance, and report the strongest contrarian or momentum cues.

Frequently Asked Questions about social-media-intelligence

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

FAQPage Schema
How do I extract trading signals from social media sentiment on Twitter and Reddit?▼

To turn social media sentiment into trading signals, you ingest messages via Twitter API and Reddit PRAW, apply weighted scoring strategies like FinBERT or VADER, and calculate buzz metrics to surface actionable momentum or contrarian cues.

What is the best way to monitor Telegram and Discord communities for financial sentiment shifts?▼

Monitoring Telegram and Discord for financial sentiment involves using Telethon and Discord bots to harvest messages and engagement, then feeding the data through sentiment scoring pipelines to generate quantified factors.

Can I use FinBERT and LLMs to score social media buzz for a quant strategy?▼

Yes, you can use FinBERT and LLMs alongside VADER to score social media buzz for a quant strategy, generating weighted sentiment factors to feed into backtests and measure IC/ICIR impact before trading.

Does this approach require compliance-aware practices when ingesting data from Twitter and Reddit?▼

Yes, ingesting Twitter and Reddit data requires compliance-aware practices. The approach provides tooling recipes for Twitter API and Reddit PRAW to harvest messages and metadata while ensuring compliant data collection.

How do I aggregate cross-platform discussion volume around a ticker for earnings backtesting?▼

To aggregate cross-platform discussion volume for earnings backtesting, you harvest messages from Twitter, Telegram, Discord, and Reddit, calculate sentiment and buzz metrics, and feed the resulting factor into your backtest to measure IC/ICIR impact.

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