The crowd prices the person before the market prices the company. Engagement sentiment for the most-watched executives and public figures, and the gap between how the crowd treats a CEO and how it treats the ticker.
Share of each figure's interactions landing on positive posts, 24-48h window, all five networks.
Same methodology on the person and on their company's ticker. A large gap either way is signal: the crowd is telling different stories about the leader and the business.
| Person | Company topic | Person + | Company + | Gap |
|---|---|---|---|---|
| Lisa Su | Advanced Micro Devices, Inc. | 88% | 10% | +78 pts |
| Tim Cook | Apple Inc. | 98% | 34% | +64 pts |
| Jamie Dimon | JPM | 15% | 72% | -57 pts |
| Andy Jassy | Amazon.com, Inc. | 7% | 51% | -43 pts |
| SUNDAR PICHAI | googl | 63% | 100% | -37 pts |
| Satya Nadella | Microsoft Corporation | 65% | 36% | +29 pts |
| Mark Zuckerberg | Meta | 53% | 29% | +24 pts |
| Elon Musk | Tesla, Inc. | 37% | 20% | +17 pts |
| Jensen Huang | NVDA | 24% | 37% | -13 pts |
Per-network sentiment score (0-100). The same person can run warm on TikTok and cold on X at the same hour; the spread column finds them.
| Name | X | TikTok | YouTube | Spread | ||
|---|---|---|---|---|---|---|
| Jamie Dimon | 27 | 33 | 90 | 82 | 100 | 84 |
| Warren Buffett | 67 | 100 | 56 | 76 | 100 | 79 |
| Jerome Powell | 66 | 38 | 71 | 65 | 100 | 62 |
| Tim Cook | 91 | 50 | 100 | 47 | 50 | 53 |
| Jensen Huang | 75 | 100 | 76 | 93 | 100 | 50 |
| Cathie Wood | 93 | 100 | 75 | 73 | 50 | 50 |
| Andy Jassy | 100 | 50 | 100 | 50 | 50 | 50 |
| Satya Nadella | 97 | 50 | 50 | 50 | 50 | 47 |
| Lisa Su | 93 | 50 | 50 | 50 | 50 | 43 |
| Sam Altman | 62 | 80 | 91 | 59 | 100 | 41 |
| MrBeast | 84 | 66 | 66 | 82 | 99 | 33 |
| Mark Zuckerberg | 83 | 82 | 93 | 81 | 100 | 19 |
| Taylor Swift | 88 | 87 | 98 | 88 | 100 | 13 |
| Elon Musk | 78 | 75 | 73 | 76 | 84 | 11 |
| SUNDAR PICHAI | 95 | – | – | – | – | 0 |
This is the observed mood of engagement, not a poll, not approval, and not a prediction. People with enormous audiences accumulate enormous neutral engagement, which suppresses every share; that is why the gap column compares like with like. Snapshot taken 2026-07-22. The commercial feed tracks the same measurement hourly, with history, for any set of people, brands, or tickers.
Every figure in this study: interactions, sentiment shares, per-network scores. No registration.
The .md file is a companion brief for AI assistants: schema, methodology, and validation anchors. Drop it into Claude or ChatGPT next to the data and your model starts from the right place.
The commercial feed runs this measurement hourly with history for any watchlist of people, brands, or tickers, with point-in-time constituent handling for universes.