{"id":760,"date":"2016-09-06T09:21:37","date_gmt":"2016-09-06T09:21:37","guid":{"rendered":"https:\/\/www.digitalnest.in\/blog\/?p=760"},"modified":"2025-01-30T11:31:04","modified_gmt":"2025-01-30T11:31:04","slug":"an-overview-of-edge-rank-algorithm","status":"publish","type":"post","link":"https:\/\/www.digitalnest.in\/blog\/an-overview-of-edge-rank-algorithm\/","title":{"rendered":"AN OVERVIEW OF EDGE RANK ALGORITHM"},"content":{"rendered":"
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Getting visibility in the news feeds of your target audience is one of the most important goals of social media strategy of any brand. It can be especially difficult on a platform like Facebook that has constantly updating algorithm to serve users the most relevant content.<\/p>\n

Edge rank was the name given to the Facebook\u2019s newsfeed algorithm years ago. Edge rank is a widely discussed topic in Facebook. The exact definition and calculation of edge rank is still a mystery. Let us see the overview of edge rank algorithm.<\/p>\n

What is an Edge?<\/strong><\/p>\n

Any activity that occurs on Facebook that can create a newsfeed story is an Edge. Whenever a friend of user posts a status update, comments on another user\u2019s status update, tags a photo, joins a page or shares a post it generates an edge.<\/p>\n

What is Edge rank?<\/strong><\/p>\n

\"\"<\/p>\n

 <\/p>\n

Edge rank depends upon three logical factors:<\/p>\n

U=Edge Affinity (audience)<\/p>\n

W=Edge Weight<\/p>\n

D=Time Decay<\/p>\n

Edge Affinity: <\/strong>Affinity score is measured by the relationship between the viewer user and the creator of the edge. The more interconnected you are, higher is the affinity score. For example if most of your friends like a similar page, there are more chances that this content will show up in your newsfeed.<\/p>\n

Edge Weight:<\/strong> There are two types of edge weight: Posts and Interactions. Edge rank takes the weight of posts into account by determining whether the post is photo, video, photo with link or text only status update. Regarding the weight of interactions measure shares and comments from a user than a simple \u201cLike\u201d and therefore they are heavily weighed and reach more users.<\/p>\n

Time Decay:<\/strong> An old story is a dead story. Time decay refers to how long has the edge has been alive. Edge rank is an ongoing score, not a one time thing. The more recent your post, the higher will be your edge rank. When a user logs into Facebook, their newsfeed is updated with the content that has the highest score at that moment.
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  Getting visibility in the news feeds of your target audience is one of the most important goals of social media strategy of any brand. It can be especially difficult on a platform like Facebook that has constantly updating algorithm to serve users the most relevant content. Edge rank was the name given to the Facebook\u2019s newsfeed algorithm years ago. Edge rank is a widely discussed topic in Facebook. The exact definition and calculation of edge rank is still a mystery. Let us see the overview of edge rank algorithm. What is an Edge? Any activity that occurs on Facebook that can create a newsfeed story is an Edge. Whenever a friend of user posts a status update, comments on another user\u2019s status update, tags a photo, joins a page or shares a post it generates an edge. What is Edge rank?   Edge rank depends upon three logical factors: U=Edge Affinity (audience) W=Edge Weight D=Time Decay Edge Affinity: Affinity score is measured by the relationship between the viewer user and the creator of the edge. The more interconnected you are, higher is the affinity score. For example if most of your friends like a similar page, there are more […]<\/p>\n","protected":false},"author":1,"featured_media":761,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"

\"\"<\/p>

\u00a0<\/p>

Getting visibility in the news feeds of your target audience is one of the most important goals of social media strategy of any brand. It can be especially difficult on a platform like Facebook that has constantly updating algorithm to serve users the most relevant content.<\/p>

Edge rank was the name given to the Facebook\u2019s newsfeed algorithm years ago. Edge rank is a widely discussed topic in Facebook. The exact definition and calculation of edge rank is still a mystery. Let us see the overview of edge rank algorithm.<\/p>

What is an Edge?<\/strong><\/p>

Any activity that occurs on Facebook that can create a newsfeed story is an Edge. Whenever a friend of user posts a status update, comments on another user\u2019s status update, tags a photo, joins a page or shares a post it generates an edge.<\/p>

What is Edge rank?<\/strong><\/p>

\"\"<\/p>

\u00a0<\/p>

Edge rank depends upon three logical factors:<\/p>

U=Edge Affinity (audience)<\/p>

W=Edge Weight<\/p>

D=Time Decay<\/p>

Edge Affinity: <\/strong>Affinity score is measured by the relationship between the viewer user and the creator of the edge. The more interconnected you are, higher is the affinity score. For example if most of your friends like a similar page, there are more chances that this content will show up in your newsfeed.<\/p>

Edge Weight:<\/strong> There are two types of edge weight: Posts and Interactions. Edge rank takes the weight of posts into account by determining whether the post is photo, video, photo with link or text only status update. Regarding the weight of interactions measure shares and comments from a user than a simple \u201cLike\u201d and therefore they are heavily weighed and reach more users.<\/p>

Time Decay:<\/strong> An old story is a dead story. Time decay refers to how long has the edge has been alive. Edge rank is an ongoing score, not a one time thing. The more recent your post, the higher will be your edge rank. When a user logs into Facebook, their newsfeed is updated with the content that has the highest score at that moment.<\/p>","_et_gb_content_width":"","episode_type":"","audio_file":"","cover_image":"","cover_image_id":"","duration":"","filesize":"","date_recorded":"","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":"","filesize_raw":"","footnotes":""},"categories":[6],"tags":[],"series":[],"class_list":["post-760","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-facebook"],"episode_featured_image":"https:\/\/www.digitalnest.in\/blog\/wp-content\/uploads\/2016\/09\/Add-headin.jpg","episode_player_image":"https:\/\/www.digitalnest.in\/blog\/wp-content\/plugins\/seriously-simple-podcasting\/assets\/images\/no-album-art.png","download_link":"","player_link":"","audio_player":false,"episode_data":{"playerMode":"light","subscribeUrls":{"apple_podcasts":{"key":"apple_podcasts","url":"","label":"Apple Podcasts","class":"apple_podcasts","icon":"apple-podcasts.png"},"stitcher":{"key":"stitcher","url":"","label":"Stitcher","class":"stitcher","icon":"stitcher.png"},"google_podcasts":{"key":"google_podcasts","url":"","label":"Google Podcasts","class":"google_podcasts","icon":"google-podcasts.png"},"spotify":{"key":"spotify","url":"","label":"Spotify","class":"spotify","icon":"spotify.png"}},"rssFeedUrl":"https:\/\/www.digitalnest.in\/blog\/feed\/podcast\/digital-nest-blog","embedCode":"

AN OVERVIEW OF EDGE RANK ALGORITHM<\/a><\/blockquote>