# $JUP Social Sentiment & Intelligence — 2026-10-07 17:20 UTC

> **Asset:** $JUP  
> **Momentum Status:** Low signal  
> **Timestamp:** 2026-10-07 17:20 UTC (2026-10-07T17:20:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-10-07-17-20/crypto/JUP  
> **Overview Brief:** https://cryptitalk.com/2026-10-07-17-20/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 1
- **Total Impressions:** 162
- **Likes:** 2
- **Retweets:** 1
- **Comments:** 3

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 3, Retweets: 1, Likes: 2, Impressions: 162


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## Cited Community Posts & Evidence


### Post #1 by @reddit
> **Author:** [@reddit](https://x.com/reddit)  
> **Metrics:** 1 likes · 0 retweets · 0 comments · 100 views  


> **Source Link:** [https://x.com/reddit/status/d84167253105339ceabe2a7d1742d593069329853d82a900861e45770cbd26c8](https://x.com/reddit/status/d84167253105339ceabe2a7d1742d593069329853d82a900861e45770cbd26c8)  


> 
> "I built a TradingView-style backtester with AI. Here is the stack and the build prompt.

I wanted a replay and backtesting workflow I could customize, so I built one with AI coding tools. The starting stack: - TradingView Lightweight Charts for the chart UI - Public APIs for live data and Databento for futures history - Python/FastAPI and DuckDB for a local implementation - A replay engine that hides future candles and steps forward one bar at a time I put together a 4:30 tutorial showing the stack, my replay workflow, analytics and how I describe strategy rules to Claude. The full build prompt is in the video description: https://youtu.be/_J51OuwtPWw"




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## Contributing Accounts

- `@MikeTheGambler_` (https://x.com/MikeTheGambler_)