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EdgeRank – How Facebook Content is Ranked

Written on Jul 12 2012

EdgeRank isn’t easy to understand for those who might not know how content is perpetuated on Facebook. It’s an algorithm used to rank content based on engagement and relevancy – it’s what determines what goes viral and what flops.

It actually takes your likes and interests and your friend’s likes and interests, then uses them to populate a ‘virtual agenda’ – determining what appears in your News Feed. It also takes into account your interactions and delivers you updates about your most visited pages and friends. You can always change what appears in your News Feed by change a subscription status of a friend or disliking a page.

Each interaction is an ‘edge':

  • a status update / liking a status update
  • uploading a photo / sharing a photo

The EdgeRank  algorithm is based on a combination of three factors:

Affinity

A score based on the proximity or how ‘friendly’ you are with someone – determined by how often do you visit their timeline or interact with them. The more you do that, the more often their updates will appear in your News Feed.

The effect is two-way – if you interact with someone, they are likely to interact with you back which will raise your affinity to them.

Edge Weight

A decision formula based on your actions. It actually determines which pieces of content are more likely to appear in your News Feed.

Each interaction carries a different weight. For example, liking photos is more important that liking a page – but liking a photo from a page carries different weight than liking a photo from a friend. The three types of content which are recognized to have the heaviest weight are Videos, Photos, and Links.

Heavier weight means more likelihood of interaction, which in turn raises affinity.

Recency

A formula based on time and decay. No matter how much the content’s EdgeRank is impacted by Affinity and Weight, content becomes less likely to appear as it ages. This means that observing the best time to post content to recieve the most interaction is important.

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One Response to this article

  1. By Buzogany Laszlo on July 22, 2012, 7:33 PM

    It is good to know! 😉

    Reply

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