Tiktok de centralized traffic distribution mechanism

1. Tiktok tiktok is the main channel to build the future customer, and the maximum drainage efficiency can be achieved by using the red bull period of shaking. It needs to start from the following aspects:
1, the
certified voice recognition is highly recommended. The annual fee of tiktok is 300 yuan. If it is a proct for weight loss, it can be certified as a sports, food, nutrition and other nature account, and better attract some fans who need to slim down. Br />
two, mining content
roughly tiktok short videos are of 12 main categories. Among them, the most popular ones are imitation, funny paragraph, talent show and so on. These short videos are hard to relate to procts, and such content is very much on the platform, and the flow is diluted very much. Therefore, it is recommended that businesses output valuable and in-depth content, such as life knowledge, operation skills, etc. these high-quality content are more in line with the operation direction of the platform side, easy to get weighted recommendation, and the account number is also relatively valuable
three, content publishing and exposure
content release time is very important. Users who are online are usually 18-22 points on Friday night, tiktok two days, holidays and other working days. Choosing to release them at a lot of time will ensure that your work will be seen by more people and the fire will be faster!
of course, no matter how good the content is, it needs exposure to attract powder. The best way to get exposure is to use the platform to recommend popular content. The tiktok tiktok control software is added to the jitter recommendation algorithm, which can control hundreds of accounts or hundreds of thousands of accounts at the same time. By continuously giving short video content through the actions of point, commentary, forwarding, etc., the whole network can be searched for 20000+ live powder within a day. And it can also help account content popular, increase account weight.

2. What is the algorithm for tiktok? TikTok Technology Co., Ltd. Tianjin

simply put forward: the algorithm of shaking is actually a funnel mechanism, which is basically consistent with the principle of recommendation algorithm of the headline's de centralization. Tiktok / BR > it has three tiktok steps:
first, cold start flow cell exposure
assume that 1 million people are uploading short videos every day on the jitter, and the jitter will randomly assign each cold video to a cold start flow pool with average exposure. For example, after each short video is released through audit, there are an average of 1000 exposures
Second, data selection
tiktok will analyze 1000 points of exposure from 1 million short videos, analyze the data of points, attention, comment, forwarding and so on, and pick out videos with more than 10% indicators, and then distribute 100 thousand times on average. Then go to see which are like, follow, forward and comment more than 10%, and roll into the next round of larger flow pool for recommendation
Third, the boutique recommendation pool
through round after round of verification, short videos with extremely high like rate, playback completion rate, comment interaction rate and other indicators are screened out to have the opportunity to enter the boutique recommendation pool. When users open the pool, they can see videos with tens of millions of likes
all the dry goods and skills shared next are closely around the core point: by increasing the number of likes, attention, comments, forwarding rate and other indicators, we can get more accurate official recommendations and win more exposure.

3. Tiktok is a de centralized algorithm platform, which means that any account has the opportunity to have millions of fans and even millions of fans. Even if we don't have any traffic, as long as our content is popular, more and more people will pay attention to it. So if you do the content in the right way, you can earn the first barrel of gold in the tiktok. If you don't know anything, please ask me in private

4. We study how to shake the voice on the tiktok. Tiktok tiktok tiktok br />
the advantages of the algorithm of

understand the recommended algorithm of shaking, so that we can do the jitter. So before that, we need to understand its benefits, in order to grasp the proction direction of 15 second video content

flow de centralization algorithm

how to tiktok? The tiktok algorithm is very attractive, and what makes it tiktok is that the traffic assignment of the jitter is decentralized. Tiktok recommendation algorithm logic can be divided into three parts:

1. Smart distribution

jitter is a proct of today's tiktok series, and headline procts are always different from other Internet procts in centralized traffic distribution. They are decentralized traffic allocation mechanisms.

for example, Weibo is a centralized traffic distribution, and no one pays attention to the fans who just opened Weibo. And even tiktok, even 0 fans, can distribute dozens of videos or even hundreds of small videos.

5. 1-5000-100: that is to say, you'd better play more than 5000 videos within one hour, and if you like more than 100 videos, you're more likely to be recommended by the system
four dimensions: the number of finished broadcasts, the rate of likes, the number of forwards, and the number of comments and interactions
publishing time: it's best to publish at 11-13 noon, 5-7 PM, and 9-11 PM. These three periods are the peak periods of user access. After your video is published, the system will basically recommend some traffic.

6.

1、 Recommendation principle of intelligent algorithm

the essence of intelligent algorithm recommendation is to match the most interesting content for current users from an aggregate content pool

this content pool contains tens of millions of content every day, covering 15s short video, 1min long video and 5min super long video

when matching content to users, the platform mainly depends on three factors: content, users and their interest in content

How does the

system understand our creative content

when describing the content, the platform will mainly rely on keyword recognition technology: by extracting the keywords in writing and video, the content will be roughly classified according to the keywords, and then the classification will be refined according to the keywords in the subdivision field

for example, the keywords of video and content are "Ronaldo, football, World Cup"

most of the key words belong to sports vocabulary. You will first classify your works into sports categories, and then subdivide them into "football", "international football" and other secondary and tertiary categories according to the specific key words

user characterization

through this series of comparison and analysis, the system speculates and restores the basic attributes of a user, for example: TA may be a male who is traveling and likes football, car and other categories

the system will classify the above user characteristics as the user's tag

User tags are mainly divided into three categories:

1) basic information of users (age, gender, region)

2) user's behavior information (attention account number, history wandering record, like collection content, music, topic)

3) reading interest (reading behavior, user clustering, user tagging)

according to the user's information and behavior, the system analyzes and calculates the user's classification, topics, people and other information, so as to complete the system's characterization of users

the essence of recommendation algorithm

uses the characteristics of works (keywords, labels, popularity, forwarding, timeliness, similarity), user preferences (short-term click behavior, interest, occupation, age, gender, etc.), and environmental factors (region, time, weather, network environment) to fit a function of user satisfaction with content, It will estimate the user's click probability for each work, and then rank all the works according to their interests from tens of millions of content flow pools in the system. The top 10 works will stand out at this time and be recommended to the user's mobile phone for display

it's probably like this. If you want to learn, you can write to Xiaobian in private

7. Tiktok algorithm is actually a funnel mechanism, which is basically consistent with the principle of recommendation algorithm of the headline's de centralization. Tiktok tiktok is divided into three steps:

first, cold start flow cell exposure

suppose that 1 million people upload short videos every day on the shaking, and the jitter will randomly assign each cold video to a cold start flow pool with an average exposure. For example, after each short video is sent out by auditing, there are 1000 exposures

second on average. Data selection

tiktok will analyze 1000 points of the 1 million short videos, analyze the data of each dimension such as point, attention, comment, forwarding and so on, and then pick out videos with more than 10% indexes, and then distribute 100 thousand times on average. Then go to see which are like, follow, forward and comment more than 10%, and roll into the next round of larger flow pool for recommendation

thirdly, the boutique recommendation pool

through round after round of verification, short videos with extremely high liking rate, playback completion rate, comment interaction rate and other indicators are screened out to have the opportunity to enter the boutique recommendation pool. When users open the pool, they see videos with tens of millions of likes< br />
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