Finally Facebook explained its “Facebook Algorithm” in detail focusing the discussion on what they termed as “Edgerank”. Unlike the search engine giant Google’s algorithm for ranking search results, Facebook’s Edgerank algorithm breaks every piece of content to an object and every interaction with the said content is an “edge” and hence the term “edgerank”.
Facebook has a secret formula to calculate the reach of your content to its audience. The process may sound complicated at the first instance but if given a second thought it’s actually quite logical. Facebook simply gives more weightage to content with more interaction. For example, the more “LIKES” a post receives, the more people interacting with it and the more private interaction resulting from it has more weightage and probability of displaying on user’s page increases. We might not be realizing the fact that Facebook’s News feed only displays a subset of the posts having higher Edgerank generated by our friends which gave birth to the concept of “News Feed Optimization” and it’s success is determined by Edgerank. It would be overwhelming if the news feed showed all the possible stories from your friends. By optimizing for EdgeRank you will always have the chance to increase the effectiveness of your Facebook posts, yielding better returns in the long run.
How does EdgeRank work?
Each Edge has three components contributing to Facebook’s algorithm:
1) Affinity Score: It means how well a particular user viewing the post is connceted to the Edge. For example, if you are friend with your brother and sister on Facebook and you post frequently on their walls and have a good number of mutual friends among you then you have a very high affinity score with your brother and sister as Facebook assumes that you’ll probably check their updates frequently.
Affinity score measure not only your actions for a post but your friend’s action and their friend’s action. For example, if you comment on a page, it’s more worthy if your friend comment on the same which is even worth more than if a friend of a friend commented on the same page. All friend’s action in your network are not treated equally. If you LIKE on someone’s status update on a regular bais and write on their wall regularly, according to Facebook that friend’s action will influence your affinity score significantly than another friend who is not in your regular communication list.
Moreover if the interaction with your friend is on the lesser side who used to be in regular touch with you then that will affect your affinity score. Technically Facebook multiplies each action by 1/x, where the value of x is the time since the action happened.
2) Edge Weight: Each and every edge has a different weight associated to it. A comment to a profile / page surely has more weight than a LIKE on the same. Again, photos and videos have a higher edge than simple links.
Generally the new Facebook features have a have a higher Edge weight to promote the features among the users. For example, check-ins by default had a very high weight when Facebook Places was introduced; if you have noticed for the first few months your news feed was probably flooded with feeds like “Person A checked into X, Person B checked into Y and so on.
Time Decay: TIME is the most oblivious factor – the older an Edge is the less weight is has. Today’s comment will obviously have more relevancy than last week’s or months. It also focuses on the following factors:
- when the user last logged into Facebook
- how frequently the user logged into Facebook
Optimizing my fan page for EdgeRank
- Publish your content as a question / poll that compels your fans to engage.
- Different researches proved that a Facebook page gets more fan interaction from photos than links, text updates or videos.
- The new post-targeting feature which was earlier available only to advertisers and yet to be rolled out to all Facebook pages allows you to target your fans by criteria which includes age, gender, genre interested in and the old options like language, country, state and city.
Facebook developers have confirmed that there are still certain aspects of Facebook Edgerank which weren’t unveiled yet. Meanwhile let’s continue to optimize the posts based on the features that are already in place to increase the engagement of your posts.