EdgeRank, the Facebook algorithm launched in 2013, aims to show users quality content that might interest them first. It determines the visibility of publications by prioritizing them. This algorithm has of course evolved since its launch; however, Facebook communicates very little about it. We know, however, that it is composed of several ranking systems and is based on four main variables to predict which publications will be the most relevant for each user:
-The type of content
-User relationships to predict which posts will be most relevant to each user.
Launched in 2016 on the same basis as Facebook, Instagram's algorithm is based on several variables:
-Interest in a publication
-The relationship with the user
-The frequency of publication
-The number of subscribers
-The level of use.
The operation of the Instagram algorithm is very often criticized, the application has just released (March 24) its chronological feed, as well as the subscription and favorites, feature to control it. It allows you to see all the publications of your subscriptions starting with the most recent.
The LinkedIn algorithm is presented by relevance. It is based on four variables, similar to those of Facebook:
-The level of interaction
-Human intervention by LinkedIn employees for active communities on the platform.
The algorithm of LinkedIn, which is a professional social network, differs from other social networks because it will favor the length of the content. LinkedIn has also increased the volume of characters from 1300 to 3000, the equivalent of a small article.
On Twitter, everything goes very fast! In 2021, 5787 tweets were published per second. On average, 50% of tweet engagement occurs within 20 minutes of posting. Then, it is very quickly drowned in the mass.
The Twitter algorithm is therefore based primarily on its recency, but also on its relevance with the keywords, its level of engagement linked to the number of retweets, and the type of media used.
There are several algorithms on YouTube:
The algorithm for home page recommendations
The algorithm for suggestions next to a video
Sdearch engine algorithm
They all work differently, and each user has their own algorithms since we do not have the same recommendations and suggestions. These are personalized according to our history, and this can go a long way since YouTube even analyzes our behavior according to the hours of the day.
When you post a video on YouTube, the algorithm will analyze its click rate and viewing time during the first 48 hours. It will also analyze the behavior of the user who watches your video: if the latter leaves YouTube to go to your website, for example, the algorithm will not highlight it because its goal is to keep the user connected if possible.
Since 2019, TikTok’s growth has been undeniable! This phenomenon is partly due to its very different algorithm. It presents us with content according to our interests and not according to the people or pages we follow. This means that we will often discover new users and new trends.
The variables on which this algorithm is based are also very different:
the number of people present in the video
where the video is shot, etc.
Meta descriptions and hashtags are also increasingly important ranking factors.