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What the picker changes
  • Top topics digest — the cards score the selected period against the prior 4 weeks.
  • 12-week heatmap & outlet matrix — show the 12 weeks ending at the selected week (they slide back with the picker, they aren’t a fixed snapshot).
  • Per-topic volume / alias drift — same 12-week trailing window, anchored on the selected period.
  • Coverage gap quadrant — scores the selected period against the 12 weeks before it (not including it).
  • Anomaly cards — only show alerts the detector fired during the selected period. Quiet weeks legitimately show none.
What stays as-is
  • Outlet orientation strip / lean colours — context-only, drawn from the last 12 weeks of activity regardless.
  • Co-occurrence graph — recent-activity anchored, not picker-driven.
  • Source & topic profiles — all-time data for the topic; the picker doesn’t affect them.
Rolling 7 days is a sliding live window for “current vibes”; switch to Weekly to compare specific weeks side-by-side.
Weekly Rolling 7 days
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Week of 8 Jun 2026
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Press topic

Fma Fraud Monitoring

1 articles · 1 aliases in press · peaked week of 26 Apr 2026 · first seen 30 Apr 2026

The article reports on a surge of deepfake scams in New Zealand using AI-generated images of public figures and financial professionals to promote fraudulent investment schemes, and raises concerns about Meta's lack of action and accountability compared to its practices in other,

Coverage by outlet lean Methodology →

Stacked weekly counts; colour by editorial lean. Stuff and The Spinoff lean centre-left, NZ Herald centre-right, others centre.

Alias drift

How press outlets have named this topic, week by week.

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Recent headlines

Most recent 1 articles linking to this topic.

Sample framings

Up to 12 framings spread across outlets. Each framing is the LLM's one-line characterisation of the article's editorial angle — not a quote.

spinoff Centre-left

regulator tracks and responds to deepfake scam ads

What will it take for Meta to do something about scams in NZ?
28 Apr
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How the public reacted

Social-media signal on the same topic, drawn from the social lens. Engagement is likes + 2×shares + 3×replies, the same weighting used across the digest cards. View on /social →

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