Recently, Facebook has explained how it ranks news feed. Facebook algorithm for news feed is based upon machine learning ranking system. It is not a single algorithm. Instead, multiple algorithms work together in phases to decide the rank.
Different things are done by diverse parts of algorithm such as candidate selection to showcase a news feed within a person’s profile. Post with misinformation and click baits are eliminated also. List is created of the friends that a person is in constant contact through the social media platform. Engaging content in the topics that the person has interest is generally noted. Using all these factors, rank of Facebook news feed post is created.
To decide about a relevant content, diverse layers are applied. Goal of an algorithm is to select the post in which the user has interest and ranked them accordingly also. Thousands of signals for Facebook ranking can be observed. Here are few examples for you.
Signals for Facebook News Feed Ranking
1. Facebook Post Characteristics
Characteristics of a Facebook post are a signal definitely for deciding ranks of news feed. Both quality and feature of the post determines whether it is a kind of content in which the users are interested in.
In case of a colorful picture, if a user has interacted with such posts in the past then it may be ranked higher. Same can be seen with the videos also.
2. Time
Based on the fact whether a post has been recently made, rank on the Facebook News Feed can be decided also. So, ’when a post has been made’ is also a ranking factor. On the occasion, characteristics of a post may be looked at such as tagged people in picture and post time to decide if a user may like the post or not.
Looking at the time of sharing post, ranking factor is decided quite often. Patent of selecting and presenting a news story can be seen for identifying the external content of social network system.
In addition to the association and interaction with the new story according to the chronological data, recent stories are generally rankled higher within the Facebook News Feed.
If same story is posted in different parts of the day then it may able to reach diverse kinds of audiences.
3. Engagement and Interest
Importance must be given on the fact also whether a Facebook user is interested to interact with certain kind of content. Different signals may be utilized to make a decision on the issue. Past posts are generally utilized as an example on the occasion.
Machine learning model is utilized to determine diverse things. It is possible to find a model that helps to determine whether the post may able to derive a comment from the users. So, Facebook news feed ranking may completely depend on the personality of the user and the choices made.