What is GraphRank?
GraphRank is a subset of EdgeRank. It is made up of Coefficient (or Affinity), Weight, Interactions (most likely similar to interactive Edges in EdgeRank), and Time Decay. The equation is most likely nearly identical to EdgeRank. Coefficient (or Affinity) is the relationship between users who share several interests, or have high activity between the two.
Facebook’s CTO Bret Taylor describes GraphRank as “a personalized view of you and your friends’ interests”. GraphRank will be of tremendous value to Facebook App Developers attempting to crack into the News Feed. As for Facebook Marketers utilizing their Facebook Page, EdgeRank is still the most important “rank” to worry about.
GraphRank will determine which Apps (Spotify, Netflix, etc) are able to crack the news feed. GraphRank is exclusively beneficial for App Developers attempting to gain exposure through the News Feed. One unique aspect of GraphRank is it’s ability to alter based on your Friends List. For example it may display your friends music preferences as opposed to your family’s music preferences.
Let’s take two example objects in Facebook:
- Object A (from Netflix): “5 friends have watched movies with Johnny Depp starring”
- Object B (from EdgeRank Checker): “How many people are a fan of Johnny Depp?”
Object A would be influenced by GraphRank, which will determine the likelihood of it reaching your news feed. If you’ve ‘watched’ Johnny Depp in the past, your affinity with this update maybe higher. Your high affinity will increase the GraphRank of this object, which may result in it’s inclusion in your News Feed. Object A comes from an App (Netflix) which is why it’s influenced by GraphRank.
Object B would be influenced by EdgeRank, which will determine the likelihood of it reaching your news feed. Depending on the EdgeRank of the Object (affinity, weight, time decay), will alter the likelihood of reaching your news feed. Object B comes from a Facebook Page (EdgeRank Checker) which is why it’s influenced by EdgeRank.
There is also a multiplier on top of GraphRank that is applied to users that are interested in same interests, near same location, or fan of same place. We expect this similar aspect to be taken into account for EdgeRank in the near future.