[Updated: 11/8/11 10:00AM ET] // Added full infographic //
A month has passed since the new hybrid news feed has been implemented. We’ve analyzed the data comparing the month before and the month after the implementation, similar to our two preliminary reports (1 Week After & 2 Weeks After). Analyzing the data in a similar fashion, we found that the general trends stayed intact: Continue reading
Facebook is unveiling new features at f8, we’re blogging on how the developments affect EdgeRank.
[1:40pm EST] Facebook is opening the Open Graph to allow for verbs & nouns meaning users can not only ‘like’ objects, they can ‘read’, ‘watch’, ‘listen’, anything. This will create a new web of data to understand and provide interesting data back to the typical Facebook user. They will be using GraphRank to help Facebook users find cool & interesting content. Most objects that will be created in this new expanded Open Graph, Zuckerburg explains they will most likely reside in the new Real Time Ticker. However, Mark mentions that the News Feed will detect “interesting patterns” to help identify which objects in the news feed should be highlighted as ‘Top Stories’. Facebook will most likely use the new Open Graph connections (books, tv, movies, music, etc) as measures of Affinity between two users. For example if two users have both watched ‘The Godfather’, we would expect the Affinity between the two users to be higher. This will create a much more dynamic measurement of Affinity between all Facebook users. Continue reading
We detailed our experience with beta access to Facebook’s testing of the new news feed. Facebook has officially unveiled the new news feed to all users as of 9/21/11. Feedback is starting to come in, however this time Facebook has provided context to all of the new changes. We’ll look at the new feed and how it will affect EdgeRank.
Facebook describes top stories as:
We determine whether something is a top story based on lots of factors, including your relationship to the person who posted the story, how many comments and likes it got, what type of story it is, etc. For example, a friend’s status update that might not normally be a top story may become a top story after many other friends comment on it.