Tom Willis WV US Inactive
Tom Willis Victory
Ad copy
The Biden–Capito Afghan Refugee Resettlement Program was not compassion done right. It was negligence disguised as policy. Proper vetting and oversight were abandoned under this $13 billion resettlement effort. That negligence resulted in a tragic outcome.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 27.4/100 |
| Spend / Reach / Long. / Eff. | 0.0 · 43.0 · 1.7 · 65.1 |
| Spend range | <USD 99 |
| Impressions | 3,000 – 3,999 |
| CPM (≈ $/1k impr) | USD 14.14 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 7 (2026-02-11 → 2026-02-18) |
| Created | 2026-02-11 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
🧠 AI analysis
| Issue | immigration |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | veterans military |
| Symbols | military |
| Call to action | none |
| Standout element | Social media screenshot of candidate's own tweet embedded alongside a photo of military personnel in a foreign landscape, creating a credibility-reinforcing mirror effect |
| Tactic | The ad uses a self-referential screenshot tactic to lend authenticity to attack claims, framing bipartisan negligence as a direct threat to West Virginia's National Guard to trigger fear and outrage. |
Where it ran (delivery by region)
| West Virginia | 91.5% |
| Pennsylvania | 1.2% |
| Virginia | 1.0% |
| Ohio | 1.0% |
| Maryland | 0.8% |
| Kentucky | 0.8% |
| North Carolina | 0.7% |
Who saw it (delivery)
| 18-24 · female | 0.8% |
| 45-54 · male | 9.9% |
| 65+ · male | 15.6% |
| 65+ · female | 16.2% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 14.2% |
| 55-64 · female | 11.0% |
| 45-54 · unknown | 0.0% |
| 45-54 · female | 5.3% |
| 18-24 · male | 4.2% |
| 35-44 · unknown | 0.2% |
| 35-44 · male | 8.9% |
| 35-44 · female | 2.5% |
| 25-34 · male | 9.1% |
| 25-34 · female | 1.7% |
| 18-24 · unknown | 0.0% |
| 65+ · unknown | 0.2% |
