How Does the Facebook Algorithm Work?

How Does the Facebook Algorithm Work?

Want to know how does Facebook’s algorithm work?

You are right. After all, this is a fundamental element that determines the distribution of your posts on Facebook.

If today the mission of Facebook is to connect users with each other, the objective of the Facebook algorithm is to offer the most interesting content to maintain / increase the retention rate of users on the platform.

In this article, you will learn what is the Facebook algorithm, what are the 4 main criteria, what are the significant interactions or the passive / active signals, and 3 good practices recommended by Facebook.

# 1. What is the Facebook algorithm?

Facebook’s algorithm is the system that determines the visibility and establishes the display order of publications in the news feed for each user.

Any member therefore has a unique news feed or are selected for him posts shared by profiles, pages and groups.

Keep in mind an important point.

If the default news feed is sorted by Facebook’s algorithm, however, a user can choose to switch to a news feed view based on the most recent posts.

In addition, he is also able to modify the preferences of his news feed by personalizing it according to his choices and not those of the algorithm.

# 2. How does the Facebook algorithm work?

Facebook continually changes its algorithm to adapt and improve it.

Over the years, some updates have been more important than others.

Today, among the 100,000+ criteria analyzed, Facebook’s algorithm pays close attention to the following 4 factors: inventory, signals, predictions and score.

2.1. Inventory

The inventory represents the stock of available content that can be displayed to a user on their Facebook news feed.

It includes all the publications issued by the profiles to which it is connected, the pages followed and the groups to which it is subscribed.

2.2. Signals

Signals relate to content information, such as for example the author of the publication, the time it was published …

2.3. Predictions

The predictions consider the likelihood that the user likes, comments or shares the post.

2.4. The scores

The score represents a rating assigned to a content according to the possibility that the user responds positively to it.

# 3. Signals and significant interactions

The algorithm studies many signals but not all of these signals are equal.

Remember. In 2018, Mark Zukerberg, put the emphasis on meaningful interactions in a publication of his Facebook profile.

This terminology takes on its full meaning now.

At a 2018 media webinar, Facebook specifies the signals taken into account before and after the announced algorithm change.




As you can guess, the signals in blue have a greater weight.

Facebook gives some examples of significant interactions :

  • One person comments or likes another person’s post (photo or status)
  • A person reacts to the post of a page that a friend shared
  • Several people respond to each other in the comments following a video or an article they have seen in the news feed
  • A person shares a link in Messenger to start a conversation with a group of friends

Note that the signals can be divided into 2 categories :

  • Passive signals : type of publication, time of publication, viewing time, etc.
  • Active signals : comments, likes, shares

# 4. Three good practices recommended by Facebook

Facebook recommends 3 good practices:

4.1. Promote meaningful interactions

The social network advocates the use of stories and videos to spark conversations between people and among page followers.

You want your content to inspire people to comment, chat with each other, or share your post.

4.2. Focus on your audience

On the one hand, it is desirable that your content is relevant to your audience.

On the other hand, your efforts must focus on building a real community.

4.3. Do not use the “engagement bait”

Finally, forget about the “engagement bait”.

This technique consists of artificially increase the engagement rate of your publications by encouraging users to use interface elements or certain native features.


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