How the RUclips algorithm influences recommended videos The recommendation stream is a two-fold process for the algorithm. First, it ranks videos by assigning them a score based on performance analytics data. (Scroll down for my list of all known factors.) Second, it matches videos to people based on their watch history, and what similar people have watched. The idea is not to identify “good” videos, but to match viewers with videos that they want to watch. The end goal is that they spend as much time as possible on the platform (and therefore see as many ads as possible.) When it ranks a video, the algorithm looks at performance: Whether people click on a video (a.k.a. impressions vs. views: thumbnail, and title are important, here) How much time people spend watching a video (watch time, or retention) How many likes, dislikes, comments or shares a video gets (a.k.a. engagement) How quickly a video’s popularity snowballs, or doesn’t (this is called view velocity, rate of growth) How new a video is (new videos may get extra attention in order to give them a chance to snowball) How often a channel uploads new videos How much time people spend on the platform after watching a video (session time) When it matches a video to a potential viewer, the algorithm looks at personalization: Which channels and topics have they watched in the past? What have they engaged with in the past? How much time do they spend watching? How many times has this video already been surfaced for this person? What don’t they watch? This video is no exception to this and has been chosen by the all mighty RUclips algorithm
Me thinking my blush moment like when my best friend jack is here tp get my water and then he try to hug me by i dodge and he said i guess you dont want a hug but i hug him and our face is red
How the RUclips algorithm influences recommended videos
The recommendation stream is a two-fold process for the algorithm.
First, it ranks videos by assigning them a score based on performance analytics data. (Scroll down for my list of all known factors.)
Second, it matches videos to people based on their watch history, and what similar people have watched.
The idea is not to identify “good” videos, but to match viewers with videos that they want to watch. The end goal is that they spend as much time as possible on the platform (and therefore see as many ads as possible.)
When it ranks a video, the algorithm looks at performance:
Whether people click on a video (a.k.a. impressions vs. views: thumbnail, and title are important, here)
How much time people spend watching a video (watch time, or retention)
How many likes, dislikes, comments or shares a video gets (a.k.a. engagement)
How quickly a video’s popularity snowballs, or doesn’t (this is called view velocity, rate of growth)
How new a video is (new videos may get extra attention in order to give them a chance to snowball)
How often a channel uploads new videos
How much time people spend on the platform after watching a video (session time) When it matches a video to a potential viewer, the algorithm looks at personalization:
Which channels and topics have they watched in the past?
What have they engaged with in the past? How much time do they spend watching?
How many times has this video already been surfaced for this person?
What don’t they watch?
This video is no exception to this and has been chosen by the all mighty RUclips algorithm
WTH
Kinda weird place to flex that knowledge but ok. How have you discovered this information??
wierd flex but fire
I heard this song a lot on tiktok
here before this blows up lol
Me seeing clips of Spider-Man being goofy💀☠️☠️
This is amazing !
i want to play a game of tag
Me thinking my blush moment like when my best friend jack is here tp get my water and then he try to hug me by i dodge and he said i guess you dont want a hug but i hug him and our face is red
what the fuck dude
What the actual fuck man
Don't watch it