Jeanne Shaheen (DEM, incumbent), Chris Pappas (DEM), Dan Innis (REP), Jared Sullivan (DEM), John Sununu (REP), Karishma Manzur (DEM), Scott Brown (REP).
83 ads analyzed, 47 with at least one technique in the copy.
Newest first. The paid-for-by line is the advertiser's own filing.
Findings
As of 2026-09-23. Counts are of distinct ads; the same text run many times is one ad.
Ads analyzed
83 (Meta 74, YouTube 9) · started running between 2026-01-23 and 2026-09-22
With at least one technique
47 of 83 (57%)
Most common techniques
Appeal to Prejudice · 30 adsLoaded Language · 30 adsGlittering Generalities · 23 ads
Meta
43 of 74 (58%) flagged · Appeal to Prejudice (26), Loaded Language (26), Glittering Generalities (22)
YouTube
4 of 9 flagged · Appeal to Prejudice (4), Loaded Language (4), Card Stacking (3)
Reported Meta spend
$151,600–210,144 on all ads, $118,200–151,454 on flagged ads · Meta reports ranges; these are the sums of their ends
Example
“sold us out in New Hampshire” — Appeal to Prejudice, paid for by WINSENATE
· the flagged ad with the highest reported spend that shows the most common technique
Money in this race
From FEC filings for 2025–26. Outside spending is money a group spends on its own about a candidate — TV and online ads, mail, canvassing. It is not a donation to the campaign, and the candidate does not control it. Supporting means it was spent to help that candidate win; Opposing means it was spent to defeat them, usually on attack ads. Groups report it within 24 or 48 hours as the election nears. Raised is the campaign's own fundraising, as of its latest quarterly report. Largest donors come from each outside spender's own FEC receipts, with each donor's share of its itemized receipts; donors under $100,000 are not named.
Jeanne Shaheen (DEM, incumbent)
Raised
$173K through 2026-06-30individuals $101K · PACs $55K · cash on hand $872K
Outside spending
none reported
Bundled through PACs
none reported · FEC bulk data of 2026-09-20
20 PACs gave directly — alphabetical; the legal limit is $5,000 per election
AEROVIRONMENT, INC. PAC $2,500
AMERICAN PISTACHIO GROWERS PISTACHIO POLITICAL ACTION COMMITTEE $3,000
AMERICAN PROPERTY CASUALTY INSURANCE ASSOCIATION POLITICAL ACTION COMMITTEE $2,500
AMERICAN SENIORS HOUSING ASSOCIATION (SENIORS HOUSING PAC) $2,500
ASTRANIS SPACE TECHNOLOGIES PAC $500
CACI INTERNATIONAL INC. POLITICAL ACTION COMMITTEE $3,300
DELL TECHNOLOGIES, INC. POLITICAL ACTION COMMITTEE $7,500
GENERAL DYNAMICS CORPORATION POLITICAL ACTION COMMITTEE (GDC PAC) $1,000
HEALTHCARE DISTRIBUTION ALLIANCE PAC $1,000
LANTHEUS HOLDINGS INC POLITICAL ACTION COMMITTEE $2,500
MEDICAL DEVICE MANUFACTURERS ASSOCIATION PAC $3,000
MORTGAGE BANKERS ASSOCIATION POLITICAL ACTION COMMITTEE $5,000
NATIONAL ASSOCIATION OF REALTORS POLITICAL ACTION COMMITTEE $3,000
NOVOCURE INC. PAC (A.K.A. NOVOCURE PAC) $2,500
OLSSON FRANK WEEDA TERMAN MATZ PC PAC $500
OPTION CARE HEALTH, INC. PAC $2,000
PFIZER INC. PAC $5,000
PRICEWATERHOUSECOOPERS POLITICAL ACTION COMMITTEE $5,000
NO GOING BACK PAC INC.— $3.5M opposing PappasSLF PAC— $3.0M opposing PappasLargest donors: ONE NATION $70.7M (28%); ADELSON, MIRIAM $30.0M (12%); SCHWARZMAN, STEPHEN A. $17.0M (7%); SINGER, PAUL ELLIOTT $14.5M (6%); MUSK, ELON $10.0M (4%)AMERICANS FOR PROSPERITY ACTION, INC. (AFP ACTION) DBA CVA ACTION AND DBA LIBRE ACTION— $2.7M opposing Pappas
· 2 ads on this pageLargest donors: KOCH INC $30.0M (33%); STAND TOGETHER INC. $20.0M (22%); WALTON, JIM C. $7.0M (8%); WALTON, S ROBSON $7.0M (8%); STAND TOGETHER CHAMBER OF COMMERCE INC $6.5M (7%)AMERICA PAC— $484K opposing Pappas
· 1 ad on this pageLargest donors: MUSK, ELON $20.1M (>99%)THE SENTINEL ACTION FUND— $426K opposing Pappas
· 3 ads on this pageLargest donors: RESTORATION OF AMERICA PAC $3.0M (18%); LEXINGTON FUND $1.5M (9%); TOWNSEND SIX CORP. $1.2M (8%); RIGHT VOTE INC. $1.0M (6%); SINGER, PAUL $750K (5%)and 8 more
Showing the 3 ads paid for by THE SENTINEL ACTION FUND. Show all 83 ads
Paid for by Sentinel Action Fundfrom 2026-09-172 variantsspend $700–89855,000–64,998 impressions
Liberal Chris Pappas says he works for New Hampshire. But his record says otherwise:
🤯 Cash payments to illegal immigrants
🤯 Amnesty for millions—even convicted criminals
Pappas is good for criminal illegals. Bad for New Hampshire.
Liberal Chris Pappas says he works for New Hampshire. But his record says otherwise:
🤯 Cash payments to illegal immigrants
🤯 Amnesty for millions—even convicted criminals
Pappas is good for criminal illegals. Bad for New Hampshire.
Liberal Chris Pappas says he works for New Hampshire. But his record says otherwise:
🤯 Cash payments to illegal immigrants
🤯 Amnesty for millions—even convicted criminals
Pappas is good for criminal illegals. Bad for New Hampshire.
Name CallingLoaded LanguageCard StackingAppeal to FearScapegoatingBlack-and-White FallacyAppeal to PrejudiceExaggeration/Hyperbole100.0% of sentences flagged
Name Calling: The label 'Liberal' is used as a derogatory political tag to prime the audience negatively before any substantive claim is made — for example: 'Liberal Chris Pappas'
Loaded Language: The phrase 'illegal immigrants' uses emotionally charged terminology to trigger a negative reaction, and 'amnesty for millions—even convicted criminals' is designed to provoke fear and outrage — for example: 'illegal immigrants', 'convicted criminals'
Card Stacking: Selectively presents two inflammatory policy positions without context, counterarguments, or verification, framing them as damning evidence of betrayal — for example: 'Cash payments to illegal immigrants', 'Amnesty for millions—even convicted criminals'
Appeal to Fear: The mention of 'convicted criminals' receiving amnesty is designed to create anxiety about public safety and override rational evaluation of the policy — for example: 'Amnesty for millions—even convicted criminals'
Scapegoating: Illegal immigrants are implicitly framed as a drain on resources and a threat, with Pappas blamed for enabling them — for example: 'Cash payments to illegal immigrants'
Black-and-White Fallacy: Presents a binary opposition: being good for one group is automatically bad for New Hampshire, allowing no nuance or middle ground — for example: 'Bad for New Hampshire'
Appeal to Prejudice: Invokes in-group identity of New Hampshire residents to imply Pappas is working against 'our people' — for example: 'Bad for New Hampshire'
Exaggeration/Hyperbole: The claim of 'Amnesty for millions—even convicted criminals' uses extreme framing to overstate the scope and danger of the policy — for example: 'Amnesty for millions—even convicted criminals'
Looks up the ad's factual claims in fact-checkers, primary sources and wire reporting. Takes up to a minute.
Paid for by Sentinel Action Fundfrom 2026-09-17spend $1,000–1,49970,000–79,999 impressions
Liberal Chris Pappas says he works for New Hampshire. But his record says otherwise:
🤯 Cash payments to illegal immigrants
🤯 Amnesty for millions—even convicted criminals
Pappas is good for criminal illegals. Bad for New Hampshire.
Name CallingLoaded LanguageAppeal to FearCard StackingScapegoatingAppeal to PrejudiceBlack-and-White Fallacy100.0% of sentences flagged
Name Calling: The label 'Liberal' is used as a derogatory political tag to prime the audience negatively before any substantive claim is made — for example: 'Liberal Chris Pappas'
Loaded Language: Emotionally charged phrases like 'illegal immigrants' and 'convicted criminals' are used to trigger fear and outrage rather than convey neutral facts — for example: 'illegal immigrants' and 'convicted criminals'
Appeal to Fear: The bullet points invoke fear by associating the politician with cash payments to illegal immigrants and amnesty for criminals, implying dangerous consequences for the public — for example: 'Amnesty for millions—even convicted criminals'
Card Stacking: The record is presented selectively through two inflammatory bullet points with no context, counterbalancing information, or nuance about the actual policy positions — for example: 'his record says otherwise' followed only by negative cherry-picked items
Scapegoating: Illegal immigrants and criminals are implicitly framed as threats that the politician is enabling, deflecting complex policy debate into blame of an out-group — for example: 'Cash payments to illegal immigrants'
Appeal to Prejudice: 'Bad for New Hampshire' invokes in-group identity of New Hampshire residents to imply Pappas is an enemy of the local community — for example: Bad for New Hampshire
Black-and-White Fallacy: The two sentences together present a binary framing: Pappas helps criminals and harms New Hampshire, leaving no room for nuance or alternative interpretation — for example: good for criminal illegals / Bad for New Hampshire
Looks up the ad's factual claims in fact-checkers, primary sources and wire reporting. Takes up to a minute.
Paid for by Sentinel Action Fundfrom 2026-09-17spend $0–998,000–8,999 impressions
Liberal Chris Pappas says he works for New Hampshire. But his record says otherwise:
🤯 Cash payments to illegal immigrants
🤯 Amnesty for millions—even convicted criminals
Pappas is good for criminal illegals. Bad for New Hampshire.
Liberal Chris Pappas says he works for New Hampshire. But his record says otherwise:
🤯 Cash payments to illegal immigrants
🤯 Amnesty for millions—even convicted criminals
Pappas is good for criminal illegals. Bad for New Hampshire.
Name CallingLoaded LanguageScapegoatingCard StackingExaggeration/HyperboleBlack-and-White FallacyAppeal to PrejudiceAppeal to Fear100.0% of sentences flagged
Name Calling: The label 'Liberal' is used as a derogatory political tag to prime the audience negatively before any substantive criticism is made — for example: 'Liberal Chris Pappas'
Loaded Language: Emotionally charged phrases like 'illegal immigrants' and 'convicted criminals' are used to trigger negative reactions rather than convey neutral facts — for example: 'Cash payments to illegal immigrants' and 'Amnesty for millions—even convicted criminals'
Scapegoating: The framing implies Pappas is enabling harm by directing resources to out-group members ('illegal immigrants', 'convicted criminals'), blaming a political figure for enabling threats to the community — for example: 'Cash payments to illegal immigrants'
Card Stacking: The bullet points selectively present characterizations of policy positions in the most alarming framing possible, omitting context, nuance, or counterarguments about the actual legislation — for example: 'Amnesty for millions—even convicted criminals'
Exaggeration/Hyperbole: The phrase 'Amnesty for millions' uses an extreme scale claim to amplify alarm beyond what a specific policy proposal would typically entail — for example: 'Amnesty for millions—even convicted criminals'
Black-and-White Fallacy: Presents a binary outcome — what is good for one group is automatically bad for New Hampshire — leaving no room for nuance or alternative interpretations — for example: 'Bad for New Hampshire'
Appeal to Prejudice: Invokes New Hampshire residents as an in-group implicitly harmed by Pappas's positions, exploiting local identity to generate opposition — for example: 'Bad for New Hampshire'
Appeal to Fear: The bullet points invoke fear by implying taxpayer money goes to illegal immigrants and that dangerous criminals would receive amnesty, designed to provoke anxiety about public safety and resources — for example: 'Amnesty for millions—even convicted criminals'
Looks up the ad's factual claims in fact-checkers, primary sources and wire reporting. Takes up to a minute.
An ad is on this page because its own "Paid for by" line is a campaign in this race; or it comes from a national Senate group and ran mostly in NH; or it ran mostly in NH and names a candidate — unless its sponsor is a campaign for some other office. Ads from outside groups appear alongside the campaigns' own.
Campaigns run one text as many separate ads. Identical text from the same sponsor is one card here, marked with its number of variants.
A technique is a specific manipulative move in the wording, found by our model and explained in one line. It is not a claim that the ad is false.
Claims are checked when a reader asks: press "Check this ad's claims" on a card. The check runs once and its result is shown to everyone afterwards. The ten ads with the most money behind them in each race are checked ahead of time.
Claim verdicts say what the cited sources say. A verdict that an ad is wrong or misleading is shown only when it cites an established fact-checker or an institutional record — Congress, a federal agency, a court — and its confidence is not low; a weaker one is not shown at all. Each verdict shows what it rests on and how confident it is. If we got one wrong, press Disagree: a verdict that readers dispute and no one defends comes down.
Video ads come from the campaigns' own YouTube channels; the transcript is analyzed. Meta ads are analyzed on their text; their video and images are not, yet.
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