Tiktok bottom logic de centralization algorithm thinking
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.
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.
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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extended materials
the ways to make money online are as follows:
1, website traffic conversion mode
< P > for advertisers to put advertisements on their own websites, so as to convert website visits into advertising revenue (this mode usually appears in the form of network alliance, such as Google Adsense, online competitive advertising, EBay, eBay's membership registration Commission, etc.)in these network alliances, Google Adsense is one of the network alliances with the largest number of websites and the highest proportion of commission. If you have your own personal website or blog and have a certain number of visits, you can obtain income by applying for Google Adsense
2. Sales commission mode
for example, websites join dangdang.com and excellence.com website alliance to promote procts for these e-commerce retail websites on their own websites. When users come to dangdang.com, excellence.com or rili mall through proct links of websites or indivial member websites and make purchases, alliance members will get a certain sales commission
3. Sales mode of online sales of procts
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extended data:
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1. Machine audit + manual double audit
when a video is initially uploaded, the platform will give you an initial flow. If after the initial flow, according to the like rate, comment rate and forwarding rate, judge whether the video is popular or not. If the first round of evaluation is popular, then it will carry out the second transmission
when you get the optimal feedback for the second time, you will get more traffic
on the contrary, in the first wave or the nth wave, if the response is not good, it will no longer be recommended. Without the recommendation of the platform, the probability of your video wanting to fire is very small, because there is no more traffic to see you. The first step of video fire is to be seen by others, the first step is to die, and the follow-up can only rely on friends' praise
the logic behind this algorithm: intelligent distribution, overlay recommendation, and heat weighting
2, overlay recommendation
the so-called overlay recommendation refers to the new video will intelligently distribute about 100vv of playback, if the forwarding amount reaches 10 (for example), the algorithm will judge as popular content, automatically weight the content, and overlay recommendation will give you 1000vv; The forwarding amount is 100 (for example), and the algorithm continues to stack up to 10000 vv; The tiktok is 1000 (for example), and then it is recommended to 10wvv, and what's more, the number of players who play the night is also more than the number of players. p>
overlay recommendation is of course based on the comprehensive weight of the content as the evaluation standard. The key indicators of the comprehensive weight are: the completion rate, the amount of likes, the amount of comments, and the amount of forwarding, and the weight of each step is different. When it reaches a certain level, the mechanism of combining big data algorithm and manual operation is adopted
3, tiktok
tiktok nearly 100 exploding flare, found all the night exploding video, and the video of the recommended voice board, the volume of the play is more than one million, and the comprehensive data (broadcast rate, point praise, comment quantity, forwarding volume) are all good except. p>
extended data:
1: improve your own data, the more complete the better. Including avatars, nicknames, mobile phones, microblogs, wechat, headlines, etc., the more detailed the better. Because it is machine and manual double audit, once the machine audit, will carry out a large number of inferior elimination
2. The video should be bright. The video is only 15 seconds. In this short 15 seconds, there is no highlight and no turning point. You will not have any interaction with you, and there is also a shielding function. Once the user blocks you, this is a very serious thing, because the user will not be recommended for your short video in the future
calculate the number of comments, reviews and shares of the audience in unit time
the specific formula is: popularity = a number of comments + B number of likes + C number of shares, coefficient a, B, C will fine tune in real time according to the overall algorithm, roughly: C & gt; A> B This step is called the first recommendation. This is why we usually see the content in the recommendation, some of the interaction rate is almost 0. Because you're the first audience of this video.