The Wall Street Journal’s deep dive into TikTok algorithms won first place in the 2021 Philip Meyer Journalism Awards from Investigative Reporters and Editors.
“The Philip Meyer award entries for 2021 showed a growing sophistication in both technique and storytelling that melds the best of social science methods and journalism,” said Sarah Cohen, a contest judge and the Knight Chair in Data Journalism at the Walter Cronkite School of Journalism at Arizona State University.
The staffers who worked on the project are Rob Barry, Yoan Cart, Dave Cole, Jason French, Robert Libetti, Maureen Linke, William Mata, Frank Matt, Darnell Stalworth, Joanna Stern, Christopher S. Stewart, Kenny Wassus, Georgia Wells, and John West.
Judges’ comments: “Reporters at the Wall Street Journal revealed how TikTok’s algorithm can send users, including teens, into a seemingly endless stream of potentially harmful videos on sex, drugs, and depression. The Journal created over 100 bots, each programmed to pause for specific types of content, to see where the social media site sent them. The bots collected hundreds of thousands of videos and thumbnail images, which were analyzed using a variety of machine learning and image classification techniques designed for unusually large collections of this kind. The reporters found in some cases, the algorithm sent the bot down a rabbit hole of dark or dangerous content.
“By presenting their first findings in a video, the Journal showed non-technical audience the threads of extreme content that the bots were pushed into viewing. The combination of simulations and analysis in uncovering this troubling and sometimes appalling content was, in the judges’ view, an important extension of the social science methods that the Philip Meyer Award is meant to recognize.”
The second- and third-place winners can be found here.
