Facebook has replaced Edgerank with the “News Feed Algorithm,” which keys on interactions, regardless of when they occur.
The new method rewards high-interest content, old and new.
Edgerank was based on these three elements: affinity, weight, and time decay.
- Affinity is affected by how users interact with your content: “likes,” comments, shares, and clicks.
- Weight is the value of those actions. For example, a comment has more weight than a “like.”
- Time decay means that the older the post, the less valuable it is, so it therefore fades out of sight.
The new algorithm ditches the time decay aspect and focuses on interactions. If an older post gets sufficient new comments, it will re-appear atop people’s news feeds.
The News Feed Algorithm responds to signals from users, including:
- How often a user interacts with the friend, page, or public figure (such as an actor or journalist) who posted;
- The number of “likes,” shares, and comments a post receives from the world at large and from your friends in particular;
- How much a user has interacted with a given type of post;
- Whether the user and others on Facebook are hiding or reporting a given post.
Early data suggest the new algorithm is increasing interaction rates. Most people just scan their News Feeds, missing relevant posts. When those posts are re-introduced to the News Feed, users have another opportunity to respond to them.
Previously, people would read 57 percent of the stories in their News Feeds, on average. They did not scroll far enough to see the other 43 percent. When those neglected stories resurfaced, that first percentage increased to 70 percent.
A version of this article first appeared on Janet Fouts.