The user’s affinity , or relationship, to the friend or Facebook Page that published the content. Users build affinity to friends and brands by interacting more frequently on their Walls with comments, Likes, shares, and tagging.
The weight for any piece of content. The more comments and Likes to a post from other friends and fans, the higher its weight. Content type — status updates, links, photos, videos, etc. –is also part of the equation.
But unless you understand the mechanics of the Facebook system – how ads and apps work together to drive traffic, then interpreting metrics like Post Quality Score, Edge Rank, Feedback Rate, action rate, conversion rate, CPC, and so forth – does it really mater what reports the tool generates? Does it matter how many ads your PPC platform can dumb multiply in the hopes that one of those ads shot into the dark will succeed. Or does it matter how many apps are in the software company’s library, such that you can compare who has the most features?
In regression, the R 2 coefficient of determination is a statistical measure of how well the regression line approximates the real data points. An R 2 of 1.0 indicates that the regression line perfectly fits the data.
1. EdgeRank Dennis Yu
2. What is EdgeRank and How does it work? <ul><ul><li>#NFO </li></ul></ul><ul><ul><li>#BWENY </li></ul></ul><ul><ul><li>@DennisYu </li></ul></ul>
3. Affinity – Weight – Time Decay
4. Affinity – Weight – Time Decay Comment Share Photo Video Wall Post Like
5. Affinity – Weight – Time Decay
7. User User Profile Increases News feed impressions 3 6 7 2 5 More interaction increases Feedback % 1 Friends User likes the page Get on the News Feed Get on Facebook Suggested Pages New Feeds Optimization 4
8. R = 0.96 Lady Gaga Barack Obama Rihanna Period: 4/21 – 5/21/2011 Top 24 Facebook Pages
10. Lane Bryant
11. More Interactions, More News Feed Coverage
12. <ul><li>70% of interactions on a post occur within one hour </li></ul><ul><li>Even more so on larger pages </li></ul>Bigger brands have earlier frequency
15. Thank you! Dennis Yu http://www.linkedin.com/in/dennisyu facebook.com/dennisyu twitter.com/dennisyu dennis-yu.com