The use of personal stories, biographical narratives, and character-driven messaging by politicians and parties to shape public perception, build voter connection, and frame policy positions during campaigns and in media coverage.
How the framings classify across 4 articles. Each framing is labelled by a small AI stance classifier; see the methodology page for details.
Up to 12 framings across outlets and orientations — each a short phrase the extractor generated to characterise the piece's editorial angle (not a quote). Filter by lean to see how each bloc is spinning the story; click through to read the original.
media-driven controversy undermining credibility
Greens’ gains in jeopardy after Mongrel Mob standblame placed on men for systemic injustice
The Left need to win back male voters the middle class woke drove into the arms of the toxic masculinity reactionary rightStacked weekly counts; colour by lean. “n/a” covers government and iwi-Māori sources where lean isn't applicable.
How this topic has been named, week by week. A new alias winning out is usually a framing shift.
How the news corpus has covered this same topic over the last 12 weeks. 3 articles from RNZ, Stuff, NZ Herald, ODT, 1News, Newsroom and The Spinoff. Click through to the press view for the full panel.
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 →
Spotted something wrong on this page? Report a correction.
