Social networks and Facebook are very important to generate traffic to our websites and gain recognition “brand” for business. (Branding in English). For this reason it is essential to enjoy a “visibility” relevant in this network and it plays an essential role Edge Rank, which is just the algorithm that uses Facebook to measure the relevance of the publications in their platform, to decide what to display in their headlines.

This algorithm is also the answer to “why having more than 1000 friends on Facebook, you only see a few updates, although none of the others have stopped using Facebook”: the difference is determined by the Edge Rank to your friends and followers. I am sure that when you enter the options you have noticed Facebook “and Latest Headlines” on the right top of the dialog box on your Home tab:

Headlines and Latest on Facebook

Pages and more Edge Rank friends who will appear in the news updates in the “Headlines” and users with a low Edge Rank can even be shown that even in the “Latest”. In addition the default when you open your Facebook homepage is “Headlines”, so unless you ask all your friends to change this option to “Most Recent” they may not know what you are sharing, if your Edge Rank is not high, since it does not qualify for “Headlines”.

For those who do business on the Internet the implications of this “detail” could make a big difference, both directly impact our presence in this social network.

But what factors measured Edge Rank? Here’s the formula:

Edge Rank

And the variables applied in the formula are explained as follows:

•     U-The degree of affinity between the user viewing the content and creating content. A higher level of greater interaction affinity.
•     W-The relevance of the content published is the second factor taken into account, and that Facebook understands that the greater the interaction of your friends list with the content you post, the better should be the quality of your publications, so assigning different scores going by the number of “Like”, the number of comments or the times that the content is shared. Different types of interaction have different weight, for example, the comments have more weight than “Like”.
•     D-News content is the third factor in the formula of the algorithm. New publications have greater weight than the “old”.

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