What is so special about TikTok's technology

The content recommendation algorithm that powers the online short video platform TikTok has once again come under the spotlight after the US ordered its Chinese owner, ByteDance, to sell the app's US assets or face a nationwide ban.

Here is how it works and why it has attracted more discussion than the technology used by its rivals such as Meta's Instagram, Google's YouTube and Snapchat.

The algorithms are deemed core to ByteDance's overall operations, and ByteDance would rather shut down the app than sell it, Reuters reported citing sources.

China 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 the app.

Before the emergence of TikTok, many had believed that technology connecting a user's social connections was the secret sauce to a successful social media app, given the popularity of Meta's Facebook and Instagram.

But TikTok showed that an algorithm, driven by the understanding of a user's interest, could be more powerful. Rather than building their algorithm on a "social graph" like Meta has, TikTok executives including CEO Shou Zi Chew have said that their algorithm is based on "interest signals".

While rivals have similar interest-based algorithms, TikTok can turbocharge the algorithm's effectiveness with the short video format, said Catalina Goanta, an associate professor at Utrecht University.

"Their recommender system is very common. But what distinguishes TikTok as an app is the design and the content," she said.

'Dynamic platform'

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 during the day.

In addition, the short video format allows TikTok to learn about user preferences at a much faster rate, said Jason Fung, former head of TikTok's gaming unit.

"Because it's in bite-size format, it is a short video, you're able to collect data about a user's preference a lot faster than YouTube, where maybe the average video is just less than 10 minutes long," he said, "Imagine you're collecting data about a user on average every 10 minutes versus every couple seconds."

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. Instagram did not launch Reels until 2020 while YouTube launched Shorts in 2021, both of which lag TikTok in years of data and product development experience.

TikTok also regularly recommends content that falls outside of users' interest, which the company's management has repeatedly said is essential to TikTok's user experience.

A study, which researchers from the US and Germany published last month, found TikTok's algorithm "exploits the user interests in 30 percent to 50 percent of the recommendation videos" after examining data from 347 TikTok users and five automated bots.

In turn, Douyin's AI was supercharged by the company's ability to leverage low labour costs in China which saw it hire many content annotators to painstakingly tag all the content and users on the platform.

While hiring annotators to tag data is now a common and important practice for AI companies, ByteDance was early in adopting this strategy.

"It's a lot of work sorting out these tags. It's very laborious," he said, "So Chinese companies have an advantage here. You can afford a lot more people. The cost is cheaper than it is for North American companies."