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How Does Facebook EdgeRank Works?

Published On - October 27, 2017

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What is Edge Rank?

EdgeRank is the Facebook’s way of prioritizing the News-feed in users profile, much like Google’s search queries shown in SERP (Search Engine Result Page). However, unlike Google, Facebook takes personal preferences of the user into consideration before presenting the information to them in a hierarchical way.

How it Works?

Facebook refers to individual posts in the news feed as Edges. It comprise of the posts that includes Comments, Likes, Shares, Clicks, Images, and Videos individually or collectively. EdgeRank is a ranking algorithm that looks at all of the Edges that are connected to the User; it then ranks each edge to understand the importance of that edge for a particular user. Edges with the highest EdgeRank will usually go to the top of the News Feed. Therefore, there are certain factors that determine how Facebook’s EdgeRank works: It comprise of Affinity, Weight and Time Decay. Let’s explore them one by one.

Affinity

edge rank

Affinity literally means liking. Therefore, Affinity is the attraction between the user and the brand. It is a one-way relationship between a User and an Edge. It shows the closeness of relationship between brand and the fan. Affinity is built by repeat interactions with a Brand’s Edges. Actions such as Commenting, Liking, Sharing, Clicking, and even Messaging can influence a User’s Affinity towards a brand, page or organization.

Weight

edge rank

Weight is a value system that Facebook assigns to increase/decrease the value of certain actions within Facebook. Commenting is more involving and therefore deemed more valuable than a Like. In the weighting system, Comments would have a higher value than a Like. In this system all Edges are assigned a value chosen by Facebook. As a general rule, it’s best to assume Edges that take the most time to accomplish tend to weigh more.

For Example, Shares have more weight than Comments; Comments have more weight than Likes; and finally Likes have more weight than Clicks. Similarly, Facebook loves videos and therefore ranks it higher when user uploads directly to Facebook instead of referring to YouTube.

EdgeRank

Thus, we can say that the general Edge Rank Formula for Weight Value is like this;
Shares > Comments > Likes > Clicks.
Videos > Photos > Status Updates > Links.

Time Decay

edge rank

Finally, Time Decay refers to how long the Edge has been active; the older it is the less value it has. Time Decay is the easiest of the factors to understand. Mathematically we can say that it is 1 divide by (Time since Last Action). As an Edge becomes older, it loses its value. Therefore, time decay allows Facebook to post fresh content on user’s News feed as opposed to the older content.

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