# $ELA Social Sentiment & Intelligence — 2026-09-20 22:40 UTC

> **Asset:** $ELA  
> **Momentum Status:** Heating Up  
> **Timestamp:** 2026-09-20 22:40 UTC (2026-09-20T22:40:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-09-20-22-40/crypto/ELA  
> **Overview Brief:** https://cryptitalk.com/2026-09-20-22-40/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 2
- **Total Impressions:** 737
- **Likes:** 20
- **Retweets:** 7
- **Comments:** 0

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 0, Retweets: 7, Likes: 20, Impressions: 737


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## Cited Community Posts & Evidence


### Post #1 by @CarOnPolymarket
> **Author:** [@CarOnPolymarket](https://x.com/CarOnPolymarket)  
> **Metrics:** 43 likes · 0 retweets · 2 comments · 3.4K views  


> **Source Link:** [https://x.com/CarOnPolymarket/status/2101783956316185059](https://x.com/CarOnPolymarket/status/2101783956316185059)  


> **Visual Context:** The chart, titled "Kalshi Combos Share Volume by Number of Legs," shows that while single legs (11+) account for 48% of reported volume, multi-leg parlays (2-10 legs) each contribute only 5-7%, supporting the post's claim that Kalshi inflates volume by counting the full multiplied payout of high-leg parlays as trading volume.  

> 
> "The Kalshi fake volume findings are getting crazier

Kalshi’s real Parlay volume is just 7.1% of reported volume.

Kalshi counts $1 placed on a 1000x parlay as $1000 volume 

Yesterday, they had $136M real trading volume vs. reported $1.91B

In a month, that would be $57B fake"


### Post #2 by @Cryptoextension
> **Author:** [@Cryptoextension](https://x.com/Cryptoextension)  
> **Metrics:** 4 likes · 0 retweets · 3 comments · 57 views  


> **Source Link:** [https://x.com/Cryptoextension/status/2101773477615481272](https://x.com/Cryptoextension/status/2101773477615481272)  


> **Visual Context:** Two workers in a cherry picker holding a black banner that reads 'AXIS ROBOTICS - THE FUTURE IS ROBOTICS' in front of a glass building.  

> 
> "Axis isn't building another robot. It's building the data engine robots actually need to learn.
Physical AI has a different problem than traditional AI. 
Robots need real experience: grasping, adapting to new environments, recovering from failure, transferring skills across"




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## Contributing Accounts

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