19 January 2026

Douyin (TikTok)'s "decentralized" algorithm

Douyin (TikTok)’s smart, personalized algorithm that delivers content uniquely for each user.

Why focus on Douyin (TikTok)’s decentralized algorithm?


Douyin’s (TikTok’s) phenomenal success is not just because short videos make it easier to share text and visual information. More importantly, it stems from Douyin’s decentralized algorithm, which strongly motivates every content creator. This is what sets Douyin apart from earlier apps like Weishi, Bilibili, and WeChat Video Channels.

 

We also believe Douyin’s decentralized algorithm is still in its early stages. In the future, more industries may adopt decentralization to incentivize creators, and the level of “decentralization” will likely become even more advanced. For this reason, I want to write an article introducing Douyin’s decentralized algorithm.

History: The Background of Douyin’s Decentralized Algorithm

 

Between 2012 and 2014, ByteDance’s Toutiao was already a highly successful product. At that time, it used an algorithm with logic similar to what Douyin would later adopt.

 

Toutiao implemented its “decentralized” algorithm by evaluating an article’s quality and recommendation value based on user completion rates:

 

Completion rate = Number of users who read the article in full ÷ Number of users who viewed the article

 

(This is similar to a video completion rate.)

 

The success of Toutiao provided a clear reference and foundation for developing Douyin’s decentralized algorithm.

 

Background

 

ByteDance’s first product: Jinri Toutiao (Today’s Headlines)

Jinri ToutiaoDouyin’s decentralized algorithm
Article completion rate → Video completion rate

Ecological principleDecentralization
Nature’s evolution has no fixed center → Decentralized

 

What is a decentralized algorithm?

 

“Decentralization” is the opposite of “centralization.”

In a centralized algorithm, one platform/organization decides what you see.

In a decentralized algorithm, users’ choices decide what gets recommended like a market economy instead of a planned economy.

 

Decentralization Analogy

 

Centralized AlgorithmPlanned Economy

  • Decided by the platform → Decided by the central government

 

Decentralized AlgorithmMarket Economy

  • Decided by users → Decided by market supply and demand

 

Algorithm –  Centralized – Decentralized

 

Economics – Planned economy (prices set centrally) – Market economy (prices set by supply and demand)

 

What problem does the “decentralized” algorithm aim to solve?

 

The “decentralized” algorithm mainly solves traffic monopoly.Instead of the platform deciding everything, a fair algorithm lets all creators get a chance to be seen, and lets users “vote” with their actions. This keeps the loop between users, creators, and platform healthy and active.

Comparing Douyin to traditional self-media platforms, we find that it’s not a platform where gaining followers early on guarantees success. Instead, creators need to consistently produce high-quality content to gain traffic. Therefore, whether in the past or present, for new or experienced creators, joining Douyin is fair; it’s never too late, which encourages more creators to join.

Comparison: Douyin vs. Traditional Self-Media Platforms

 

Bilibili 

 

Non-followers   

  • Rely on sharing via followers / friends
  • Platform selects some content to recommend
  • Organic search

 

Followers 

All followers can receive the push / notification

 

Douyin (Tiktok)

 

Non-followers   

Rely on the data performance of the content itself

 

Followers 

Pushed to followers first, but not every follower will receive it; recommendations still follow the step-by-step “traffic pool” mechanism.

How does Douyin (TikTok) implement a decentralized algorithm?

 

To achieve a “decentralized” recommendation algorithm, the essence is to involve every user in making choices, then collect and compare the data from these choices to arrive at a result. Of course, there isn’t a direct “vote” button for users to click; Douyin (TikTok) indirectly judges user choices by collecting interaction data from content.

 

Recommendation principle: First, provide initial traffic to the content as a data reference for the next layer of traffic recommendation, and then upgrade layer by layer.

 

Currently, the recommended traffic for each traffic pool on Douyin is roughly as follows. It’s important to note that there’s still a centralized part to the recommendation process; content that gets featured on trending topics requires manual review to filter out vulgar, politically sensitive, or illegal content.

 

Douyin Recommendation Algorithm

Initial Traffic Pool (Cold Start)
Provides the first batch of traffic to collect objective data for evaluation
≈ 200–500 impressions

 

Question:
“Is its performance data better than similar videos in this time period?”

Yes → Second-Level Traffic Pool
Evaluate based on the performance data in the second-level pool

Question again:
“Is its performance data better than similar videos in this time period?”
Yes → Third-Level Traffic Pool
Evaluate based on the third-level pool data

Question again:
“Is its performance data better than similar videos in this time period?”
Yes → Fourth-Level Traffic Pool
Evaluate based on the fourth-level pool data
No → Stop recommending
No → Stop recommending
No → Stop recommending

Review mechanism: from broad → to strict as it moves through the traffic pools.

To compare similar videos in the same period, focus first on watch time, because it matters most. Douyin rewards content that keeps users watching, so use watch time plus other basic metrics to judge performance.

 

Douyin (Tiktok)  Recommendation Algorithm

  • Filter videos
  • Read videos
  • Calculate score
  • Return results
  • Collect feedback


The Future – decentralized algorithms still have a lot of room for development, mainly in terms of horizontal and vertical integration.

To compare similar videos in the same period, focus first on watch time, because it matters most. Douyin rewards content that keeps users watching, so use watch time plus other basic metrics to judge performance.

 

Douyin (Tiktok)  Recommendation Algorithm

 

  • Filter videos
  • Read videos
  • Calculate score
  • Return results
  • Collect feedback

 

The Future – decentralized algorithms still have a lot of room for development, mainly in terms of horizontal and vertical integration.

Horizontally: human decentralization is not only applicable to short video creation scenarios.

 

In the future, music creation, data storage, finance, and other industries may all be “decentralized.” Or, in other words, areas that are monopolized and have conflicts may be “decentralized.”

 

Vertically, Douyin is “decentralized” but still has centralized parts.


Creator income is still allocated by the platform, and we can’t yet measure everyone’s real contribution to pay them perfectly fairly. In the future this may change technologies like blockchain already offer fairer, transparent reward systems, as seen with Bitcoin miners.

What’s clear is that the old era where talent had no stage is ending. With decentralized algorithms, capable people can finally be seen. Douyin (TikTok) is like an amplifier: if you’re truly good, it magnifies you. If you’re just “1,” any power is still 1; but if you’re even slightly better, like 1.1, repeated amplification will show a huge difference. And behind every “one minute on stage” still lies “ten years of practice off stage.”

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MMG Thailand is the first and only Chinese-owned Chinese marketing company in Thailand that aims to connect Sino-Thai cultures and power partners’ success. 

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