Mashable: “…Researchers Nick Hagar from the New York Times and Nicholas Diakopoulos of Northwestern University have published a study in New Media and Society [Algorithmic indifference: The dearth of news recommendations on TikTok] which investigated how news content was amplified and recommended on the TikTok For You Page. Bear in mind that at the end of 2022, the Reuters Institute of Journalism found that about half (49 percent) of the world’s top news publishers were posting on TikTok, and even more have joined since. To examine how often these publishers were being suggested to users, Hagar and Diakopoulos had to create a methodology as TikTok does not allow for API access, the tech tool that’s needed to dig deep into the platform. First they started a ‘pipeline’ to scrape recommended accounts from TikTok, beginning with accounts from The Washington Post, NBC News, National Public Radio, and PBS News. They built out a list of the ensuing recommended news-producing accounts, which had to either be news publishers, professional journalists, or news aggregators/commentators. Then 60 bots were programmed, with varying levels of news interest, to detect or determine whether to watch or skip videos based on their transcripts’ overlap with that day’s New York Times headlines. Of the 6,568 videos served up to the bots, just six fitted the authors’ classification of news…”