Nieman Lab: “Given the amount of attention TikTok has swallowed up from anyone under the age of 30, we might expect it to be a more obsessive focus of news organizations in their efforts to attract younger and more engaged audiences. But TikTok has shown itself to be rather inhospitable to news: It removes links that publishers could use to pull users out of the app, it does little to label news or help users evaluate its credibility, and unlike other apps, it’s offered few financial incentives to news publishers (though note a couple of exceptions). It’s not inevitable that TikTok is hostile terrain for news. Researchers have found that algorithmic recommendation systems like TikTok could effectively wall people off from news content — the often-voiced “filter bubble” concern — but they could also increase the chances that people are incidentally exposed to news while looking for other things. So which of these effects does TikTok’s algorithm have? And how does news fare amid the sea of content that washes over a typical TikTok user? It’s difficult to answer those questions definitively, because TikTok doesn’t make its API available to researchers, and the algorithmic experience varies widely among users. But in a new study in the journal New Media & Society, researchers Nick Hagar (now a New York Times data scientist) and Nicholas Diakopoulos of Northwestern University found a few clever ways to look at news’ role in TikTok’s algorithm.,,

The verdict? TikTok is a news wasteland. Out of the bots’ 6,568 videos, just 6(!) could be classified as news — and those were two different videos shown multiple times. Those dismal results came even though some of those bots were extremely news-interested. “The For You Page algorithm surfaces virtually no news content, even when primed with active engagement signals,” the authors concluded…”