Week 6: Networks and Friendship Paradox

I started this week’s readings off with Kieran Healy’s post, “Using Metadata to find Paul Revere”. His research into the analysis of personal metadata got me thinking of what constitutes a breach of privacy and when does a governing entity go too far in looking through our personal lives in the name of security. However, I won’t dedicate my post to any alarmist ideas or writings on the need to respect privacy any more than I already have, instead I will write about an interesting aspect of social networks that I heard about a while ago, the friendship paradox.

I originally heard about this as a short story that made it onto the daily news; it does not really have much to do with cutting edge news, but nevertheless it caught my attention. The idea behind the friendship paradox is that, on average, a person has fewer friends than their friends have. This tallying of friends is most easily done on social networking sites where there are friend lists available to immediately quantify the number of social network friends in one’s life. It is fairly easy to log onto social media sites and take a quick look to see if this is true; some of my Facebook friends have over one thousand friends each, easily outstripping me, my Instagram follows are much lower than those of the people who follow me, and a general look over Twitter shows that most people follow at least one celebrity or relatively famous account that can have thousands or even millions more followers than their own. There is actually an article available on JSTOR from the American Journal of Sociology that is dedicated to this phenomenon if you’re interested in reading more about it! If you don’t want to spend quite as much time there is a helpful Wikipedia article that presents the paradox more succinctly and seems reliable (as far as I can tell).

The friendship paradox is loosely related to our foray into network analysis, and could provide interesting data if analyzed in the same way Healy conducted his research or in other ways of analyzing networks. For example, with a sampling of one’s friends from a social media site it is possible to see if there are any other correlational elements that connect the friends with more friends to each other. Perhaps there is a relation between “popularity” on social media sites with frequent posting of statues or photos, or maybe serial posting has the opposite effect and reduces the number of friends. There may even be a specific personality type that attracts more friends that could become apparent when examining their “likes” on Facebook or hashtag patterns on other social medias.