The Facebook algorithm takes into consideration engagement interactions, relevance, timeliness, and thousands of other weighted factors in an effort to populate a user’s news feed with more of the stuff they want (as inferred by Facebook), and less of the noise.
Unlike Twitter where every tweet you make automatically enters the Timeline of every person that follows you, on Facebook the content that shows up in an individual’s News Feed is dictated by an algorithm. If someone Likes your Page (or befriends you if you have a Profile rather than a Page), you’ve simply crossed the first barrier of earning a position in that user’s News Feed.
In a sentence, the Facebook algorithm weighs factors to determine on a post-by-post basis whether a post is qualified to pass into an individual’s News Feed.
What is EdgeRank?
Like Google uses a 1-10 PageRank grading system to infer the authority and significance of web pages based on the quality and quantity of their inbound links, Facebook uses a point-based system to infer the authority and importance of Facebook Pages based on several factors – the most prominent of which is social interactions.
The Facebook algorithm score is cumulative and represents the brand’s perceived clout, both big picture and at the post level.
This News Feed filtration system – once called “EdgeRank” but now simply referred to broadly as the Facebook algorithm – takes into consideration 100,000 individually weighted factors to deliver the most authoritative, relevant, and timely content to individuals.
Sheldon explains the friendship algorithm on The Big Bang Theory. His algorithm has more to do with real, in-person friendship and less to do with news feeds, but you get the idea.
Of those 100,000 considerations, the three original EdgeRank factors – Affinity, Weight, and Time – are still relevant and prominent ranking factors. In other words, EdgeRank hasn’t gone away, its principals have simply been folded into a much larger, more advanced contemporary Facebook algorithm.
4 Factors the Facebook Algorithm Takes Into Consideration
- Type of Interaction (liking, commenting, or sharing; each of the three interactions has its own weight depending on the amount of effort it takes to perform the interaction)
- Who made the interaction (how directly connected the user is to the poster based on manual friendship designations, closeness inferred by interaction, and other factors)
- What time the post was made (time decay; News Feed deserves freshness)
- Post popularity (if a post is losing the freshness edge because of time decay, but lots of people are still actively commenting on or sharing a post the engagement can trigger a hot topic bump [my name for it, not Facebook’s] that expands the post reach rather than letting it die)