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Tom Willis WV US Inactive

Tom Willis Victory

ad creative

Ad copy

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

↗ View in Meta Ad Library (the live creative — image/video/layout)

Performance proxies

Overall score36.9/100
Spend / Reach / Long. / Eff.17.4 · 61.7 · 1.4 · 66.9
Spend rangeUSD 200–299
Impressions20,000 – 24,999
CPM (≈ $/1k impr)USD 11.09
Est. audience size100,001 – 500,000
Days live6 (2026-01-13 → 2026-01-19)
Created2026-01-13
Creative variants1 body · 0 headline
Platformsfacebook, instagram
Languagesen
CandidateWV — Tom Willis
Surfaced by“senate:Tom Willis”

🧠 AI analysis

Issueimmigration
Framingattack opponent
Message typepersuasion
Emotional appealfear
Production tiersemi pro
Who picturedopponent
Symbolsborder, military
Call to actionnone
Standout elementYellow-highlighted name 'Shelley Moore Capito (R-WV)' at the bottom of the Breitbart screenshot singling her out as a betrayer
TacticThe 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.

Where it ran (delivery by region)

West Virginia92.7%
Ohio1.1%
Pennsylvania0.9%
Virginia0.7%
Kentucky0.7%
Maryland0.7%
Florida0.5%

Who saw it (delivery)

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%

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