Friend Suggestions of Facebook
https://www.theguardian.com/technology/2016/jun/29/how-does-facebook-suggest-potential-friends-not-location-data-not-now
When you sign up for Facebook, you often fill out account information in which you want to be shared with the public and also privately to Facebook. This often includes relationship status, education, past cities, and work history. Based off of this, Facebook often recommends potential friends. As well, a big part of friend suggestions comes from mutual friends. As talked about in Lecture on Graph Theory, Triadic Closure is used to connect two people who have a mutual friend. Triadic Closure is “a basic ‘principle’ in which if two people in a social network have a friend in common, they are likely to become friends at some point” (lecture 2850 Graph Theory). Facebook’s algorithms take this concept into account and use it as their main source of connecting the world.
As well, Facebook has participated in the “small world” phenomenon. In which, their social network graphing showed there are only 3.57 degrees of separation of its 16 billion users, in 2016. Meaning, on average, it would take you to get to 3.57 friend to friend relationships to get to any of the other Facebook users. This is skewed by those who have thousands and hundreds of thousands users and also by those who have only one or two friends. Their friend suggestions are aimed to make this degree lower as the more friends you have, the more likely you are to have mutual friends with someone else. Each time you add a friend, your network grows as does Facebook’s. Through triadic closure, they are decreasing their degrees of separation. As of now, I predict it is less than 3.57 degrees of separation as the time has went on 5 years later.