Susan Collins US Inactive
COLLINS FOR SENATOR
Are you alarmed by this?
STOP the Chinese illegal marijuana farms in Maine
Ad copy
It’s reported that Chinese criminal networks are building up illegal marijuana farms across Maine, and the Department of Justice has been slow to investigate this. This could be happening in your backyard, and we want to know if you are alarmed by this. Add your name to our petition before 11:59 PM tonight to let us know.
↗ View in Meta Ad Library (the live creative — image/video/layout)
Performance proxies
| Overall score | 49.9/100 |
| Spend / Reach / Long. / Eff. | 27.6 · 68.1 · 39.4 · 64.5 |
| Spend range | USD 600–699 |
| Impressions | 40,000 – 44,999 |
| CPM (≈ $/1k impr) | USD 15.28 |
| Est. audience size | 100,001 – 500,000 |
| Days live | 144 (2024-06-26 → 2024-11-17) |
| Created | 2024-06-26 |
| Creative variants | 1 body · 1 headline |
| Platforms | facebook, instagram |
| Languages | en |
| Candidate | ME — Susan Collins |
| Surfaced by | “senate:Susan Collins” |
🧠 AI analysis
| Issue | crime safety |
| Framing | issue advocacy |
| Message type | list building survey |
| Emotional appeal | fear |
| Production tier | semi pro |
| Who pictured | none |
| Symbols | farm rural |
| Call to action | sign petition |
| Standout element | Chinese flag superimposed over marijuana plants in dark red tones, fusing foreign threat imagery with local crime fear |
| Tactic | Classic fear-based list-building tactic using an urgent deadline and a localized threat narrative to harvest petition signatures while amplifying anxieties about foreign criminal activity and federal inaction. |
Where it ran (delivery by region)
| Maine | 100.0% |
| Unknown | 0.0% |
Who saw it (delivery)
| 18-24 · female | 0.4% |
| 45-54 · male | 5.5% |
| 65+ · male | 22.9% |
| 65+ · female | 29.0% |
| 55-64 · unknown | 0.3% |
| 55-64 · male | 12.9% |
| 55-64 · female | 14.3% |
| 45-54 · unknown | 0.1% |
| 45-54 · female | 5.1% |
| 18-24 · male | 1.2% |
| 35-44 · unknown | 0.1% |
| 35-44 · male | 2.6% |
| 35-44 · female | 2.2% |
| 25-34 · unknown | 0.1% |
| 25-34 · male | 1.9% |
| 25-34 · female | 1.2% |
| 18-24 · unknown | 0.1% |
| 65+ · unknown | 0.3% |
