The algorithm of the Facebook news feed is machine learning on one hand and human grasp on the other. So how much do you know about the algorithm of the Facebook news feed?
Why do you need to know the Facebook News Feed algorithm?
Facebook has 1500 messages on display, but each person’s attention is limited, and most people only read the first 300 messages.
So only by studying and understanding the algorithm of the news feed can your posted content make it to the top 300, so that more people can see your message.
At this point, some newbies may question: Isn’t the display of information sorted by time?
Facebook is now a strong relationship platform, and the news feed algorithm was introduced to give users a better experience.
How can I improve the ranking of my messages?
What actions do people take when they see a post?
- Will they like and comment on a good post when they see it?
- Will they share it with your friends?
- Do they want to follow the person?
- Will they click on favorites?
If you see a post that does not interest you：
- Do you want to hide similar messages?
- If you see content that is not allowed on the platform, will you report it?
There are different algorithms for these actions. And it also includes friends of friends, as well as a wider dimension of the algorithm, which is the edge level.
What factors are included in the algorithm of the edge level?
- Frequency of contact: contacted every day / contacted again at intervals.
- The intensity of contact: the time of contact every day / see the reply not reply.
- Bidirectionality: one-sided messages sent / continuous interaction.
- The degree of freshness
- The weight of the edge
So to get your post to the top, you need to find ways to intervene in the behavior of the user. But in the process of intervention needs to pay attention to several points.
- some users who like the post, may not be more interested in the post, the likes are just a habit.
- For the length of the post, many people read part of it and then quit, which is not sure whether the user is interested.
For these algorithms, there are many things that need to be learned in-depth, but there are some factors that cannot be solved by algorithms.