United States 2026 · Data
Every political advertiser
The 24,034 Facebook and Instagram pages that ran a domestic political ad paid in dollars from 4 May 2026, from Meta’s archive as pulled on 4 November 2026. Every page links to its own Vipima page, with its weekly spend, tone and costliest ads, and from there to Meta’s Ad Library; a party’s or candidate’s page links to that party or candidate.
Download every row as CSV · Browse by state on the map
Filtered to Illinois
458 pages · $4.8M on Illinois races
Dem. 58% · Rep. 13% · no side 29%
10 pages · 82 ads · $16.5K
| # | Page | Type | Side | Race | Result | Ads | Spend | In IL | Impressions | Attack | Last ad |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Citizens for Darby Hills | Candidate | None | None | 16 | $8.3K | $2.8K | ~1.1M | 31% | 20 Oct | |
| 2 | Representative Liish KozlowskiPaid for by Alicia 'Liish' Kozlowski | Candidate | Dem. | None | 3 | $949 | $450 | ~66.5K | 13 Jun | ||
| 3 | Elect Michael CrownerPaid for by FRIENDS OF MICHAEL CROWNER | Candidate | None | None | 8 | $896 | $447 | ~102.5K | 0.0% | 22 Oct | |
| 4 | Mike QuigleyPaid for by Representative Mike Quigley | Candidate | Dem. | None | 4 | $3.4K | $250 | ~536K | 19 Oct | ||
| 5 | State Rep. Bob RitaPaid for by Friends of Robert 'Bob" Rita | Candidate | None | None | 7 | $747 | $199 | ~86.5K | 57% | 16 Oct | |
| 6 | State Senator Darby HillsPaid for by Senator Darby Hills | Candidate | None | None | 18 | $891 | $50 | ~29K | 0.0% | 30 Sep | |
| 7 | Senator John Curran | Candidate | None | None | 9 | $446 | $50 | ~19.5K | 0.0% | 28 Aug | |
| 8 | Senator Dave SyversonPaid for by Dave Syverson | Candidate | None | None | 8 | $396 | $50 | ~11.1K | 13% | 21 Sep | |
| 9 | State Senator Seth LewisPaid for by Senator Seth Lewis | Candidate | None | None | 6 | $297 | $50 | ~11K | 0.0% | 17 Aug | |
| 10 | Mayor Matt Wigginton | Candidate | None | None | 3 | $149 | $50 | ~9.5K | 26 Oct |
Spend and impressions are midpoints of Meta’s ranges, impressions capped at “1M+” per ad. Type, side and race come from a model reading each ad; a page shows the side and race most of its spend went to. Attack is the share of a page’s classified ads that attack a named opponent, shown from five ads. See the methodology.