By Eduardo Baptista
BEIJING, Dec 20 (Reuters) – The content recommendation algorithm that powers the online short video platform TikTok has once again come under the spotlight after the app’s Chinese owner ByteDance signed binding agreements to form a joint venture that will hand control of operations of TikTok’s U.S. app to American and global investors, including cloud computing company Oracle.
Here is what we know so far about its fate, following the establishment of the joint venture.
IS BYTEDANCE CEDING CONTROL?
While the creation of this new entity marks a big step toward avoiding a U.S. ban, as well as easing trade and tech-related tensions between Washington and Beijing, there is still uncertainty surrounding the ownership of the recommendation algorithm, considered TikTok’s crown jewel.
Rush Doshi, who served at the National Security Council under President Joe Biden, said on X it was unclear whether the algorithm had been transferred, licensed or was still owned and controlled by Beijing, with Oracle merely providing “monitoring”.
The algorithm is deemed core to TikTok’s global success and until a few months ago, ByteDance’s position was that it would rather shut down the app in the U.S. than sell it.
But in September, Reuters reported, citing sources, that ByteDance would maintain ownership of TikTok’s U.S. business operations but cede control of the app’s data, content and algorithm to the joint venture.
The joint venture would serve as the back-end operation to the U.S. company and handle U.S. user data and the algorithm, sources said at the time, adding a separate division that will continue to be wholly owned by ByteDance would control the revenue-generating business operations such as e-commerce and advertising.
Those arrangements formed the deal contour announced on Thursday, two sources with knowledge of the matter told Reuters on Friday. The ByteDance-controlled TikTok U.S. entity would be the revenue-generating one, while the new joint venture will receive a portion of the revenue for its technology and data services, said the sources.
The Chinese government has yet to declare its stance on the signed deal. Beijing made changes to its export laws in 2020 that give it approval rights over any export of algorithms and source codes, adding a layer of complexity to any effort to sell or spin off the U.S. app.
WHAT MAKES THE ALGORITHM POWERFUL?
Analysts have said that it is not just the algorithms, but also how they work with the short-video format, that have made TikTok so successful globally.
But TikTok showed that an algorithm, driven by the understanding of a user’s interest, could be more powerful. Rather than building its algorithm on “social graph” like Meta has, TikTok executives have said that its algorithm is based on “interest signals”.
The short-video format enables TikTok’s algorithm to become much more dynamic and even capable of tracking changes in users’ preferences and interests across time, going as granular as what a user may like during a certain period of time during the day.
And the positioning of TikTok as an app built for mobile devices from the beginning also gave it an advantage over rival platforms that had to adapt their interfaces from computer screens.
TikTok’s early entry into the short-video market also gave the company a big early-mover advantage. Meta’s Instagram did not launch Reels until 2020 while Alphabet’s YouTube launched Shorts in 2021, both of which lag TikTok in years of data and product development experience.
WHAT DOES RESEARCH REVEAL ABOUT THE ALGORITHM?
TikTok also regularly recommends content that falls outside of users’ interests, which the company’s management has repeatedly said is essential to TikTok’s user experience.
A study, which researchers from the U.S. and Germany published last year, found TikTok’s algorithm “exploits user interests in 30% to 50% of the recommendation videos”, after examining data from 347 TikTok users and five automated bots.
“This finding indicates that the TikTok algorithm opts to recommend a large number of explore videos in an attempt to either infer better the user interests or maximise user retention by recommending many videos that are outside of the user’s (known) interests,” the researchers wrote in the paper titled “TikTok and the Art of Personalization”.
(Reporting by Eduardo Baptista; Editing by Muralikumar Anantharaman)
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