Tom Willis Victory
Sen. Shelley Moore Capito (R-WV) was one of 19 Senate Republicans who voted with Democrats to give over $13 billion to the Biden administration’s Afghan Refugee Resettlement Program. This program allowed an unlimited number of Afghan refugees to be placed across our country, including in West Virginia, without proper vetting. This program created severe national security risks. Sen. Capito's support of this program was dangerously and tragically naive, and placed our communities at risk. Read More: https://www.breitbart.com/politics/2021/12/03/the-list-19-senate-republicans-give-biden-over-13b-to-resettle-unlimited-flow-of-afghans-across-their-states/ Roll Call: https://www.senate.gov/legislative/LIS/roll_call_votes/vote1171/vote_117_1_00477.htm?congress=117&session=1&vote=00477#position
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| Overall score | 36.9/100 |
| Spend / Reach / Long. / Eff. | 17.4 · 61.7 · 1.4 · 66.9 |
| Spend range | USD 200–299 |
| Impressions | 20,000 – 24,999 |
| CPM (≈ $/1k impr) | USD 11.09 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 6 (2026-01-13 → 2026-01-19) |
| Created | 2026-01-13 |
| Creative variants | 1 body · 0 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | WV — Tom Willis |
| Surfaced by | “senate:Tom Willis” |
| Issue | immigration |
| Framing | attack opponent |
| Message type | persuasion |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | opponent |
| Symbols | border, military |
| Call to action | none |
| Standout element | Yellow-highlighted name 'Shelley Moore Capito (R-WV)' at the bottom of the Breitbart screenshot singling her out as a betrayer |
| Tactic | The ad uses a Breitbart news screenshot as borrowed credibility to frame a Republican incumbent as a traitor to her party on immigration, amplifying fear of unvetted refugees to damage her standing with the GOP base. |
| West Virginia | 92.7% |
| Ohio | 1.1% |
| Pennsylvania | 0.9% |
| Virginia | 0.7% |
| Kentucky | 0.7% |
| Maryland | 0.7% |
| Florida | 0.5% |
| 18-24 · female | 0.5% |
| 45-54 · male | 7.8% |
| 65+ · male | 23.8% |
| 65+ · female | 26.5% |
| 55-64 · unknown | 0.1% |
| 55-64 · male | 15.1% |
| 55-64 · female | 12.0% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 4.2% |
| 18-24 · male | 2.0% |
| 35-44 · unknown | 0.0% |
| 35-44 · male | 3.5% |
| 35-44 · female | 1.3% |
| 25-34 · unknown | 0.0% |
| 25-34 · male | 2.2% |
| 25-34 · female | 0.5% |
| 18-24 · unknown | 0.1% |
| 65+ · unknown | 0.3% |