Signals:

This stage is all about consideration about the content. Each post is analyzed based on the data available such as:

Number of likes, comments, shares and reactions

Type of post (video, images, written content)

Owner of post

Time and Day of post

Speed of internet connection

Type of device in use

Blocked Content

Marked as spam

Time spent on post

Top fifty interactions

Video engagement (turning on audio, changing to full-screen or HD)

The signals above are generated from the users and given weightage. For example, sharing a post (personal/public) has greater weightage than liking or reacting to it. Similarly, content from family and friends are usually weighed higher than content from pages followed depending on the information gathered.

Predictions:

The above-described data is then used to make informed decisions. The algorithm attempts to make predictions based on information available to determine what the users prefer to see on their feed, what they may hide, how probable are they to engage with it actively or ignore it. For example, a post from a friend who has previously received a comment from a user on a similar post in the past will likely be predicted to interest the user over content from a page followed that has received a like from the same user previously. If video content is seen to be receiving higher engagement over written matter or images, such posts are predicted to be preferred by the user.

Scoring:

These predicted posts in individual scenarios along with the weights are used to arrive at a relevancy score. The posts are then ordered based on this score in descending order. These posts are then delivered in the determined sequence to the news feed.

The News Feed Algorithm is thus described as a “ranking to organize” approach. 

https://www.geeksforgeeks.org/facebook-news-feed-algorithm/