# $WOLVERINU Social Sentiment & Intelligence — 2026-10-11 05:20 UTC

> **Asset:** $WOLVERINU  
> **Momentum Status:** Low signal  
> **Timestamp:** 2026-10-11 05:20 UTC (2026-10-11T05:20:00Z)  
> **Canonical URL:** https://cryptitalk.com/2026-10-11-05-20/crypto/WOLVERINU  
> **Overview Brief:** https://cryptitalk.com/2026-10-11-05-20/crypto.md  

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## 10-Minute Social Metrics
- **Posts Analyzed:** 1
- **Total Impressions:** 81
- **Likes:** 13
- **Retweets:** 6
- **Comments:** 5

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## Momentum & Sentiment Analysis
Total Engagement - Comments: 5, Retweets: 6, Likes: 13, Impressions: 81


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## Cited Community Posts & Evidence


### Post #1 by @KissonL
> **Author:** [@KissonL](https://x.com/KissonL)  
> **Metrics:** 1 likes · 0 retweets · 0 comments · 33 views  


> **Source Link:** [https://x.com/KissonL/status/2109146980588867868](https://x.com/KissonL/status/2109146980588867868)  


> **Visual Context:** A slide from State of AI 2026 titled 'The highest-earning e-commerce agent is among the worst at avoiding fraud,' detailing E-CommerceBench results showing GPT-5.6 Sol averaged CNY 1.43M year-end assets but spent 18.48% on fraudulent suppliers, while Opus 4.7 spent only 0.12%.  

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> "Alibaba and HKUST built a simulated online-shopping economy to test AI agents. Eighteen models each got ¥100,000 of starting cash and ran up to four stores for a simulated year, choosing from 6,900 products and 576 suppliers.

The model that made the most money, GPT-5.6 Sol,"




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## Contributing Accounts

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