Why “Your Facebook friends have more friends than you”

Here is an overview of an interesting quirk on Facebook: your Facebook friend likely has more friends than you do.

It’s just the digital reflection of what’s known to sociologists as the “friendship paradox.” In 1991, sociologist Scott Feld found that, generally speaking, any person’s friends tend to be more popular than they are. The reason, he said, is fairly simple: people are more likely to be friends with someone who has more friends than someone who has fewer friends.

This is true on Facebook as well, the study found. A small number of people are isolated and don’t appear on many lists, but popular people show up again and again.

Another interesting result of the study finds that Facebook users tend to get more messages, friend requests, likes and photo tags than they give, pointing to the existence of a few Facebook “power-users” driving the site’s activity.

Keith Hampton, a professor at Rutgers University and the lead author of the report, said that power users make up around 20-30 percent of Facebook’s users, and that there are three specialties within these power users. Some users send a lot of friend requests, while others most frequently “like” posts and pictures. A third kind of power user tends to make a lot of photo tags.

If you put this in social network terms, there are certain people who are nodes in the Facebook network. These nodes have more friends and are centers of information, comments, pictures, likes on Facebook, between different groups and users.

If we know this is how the world works, you could imagine how this information could be put to use. Perhaps Facebook puts information from these nodes more often in your news feeds. Perhaps marketers hope to specifically target these people as they can have a wide reach. Perhaps other users could look to connect with these nodes, knowing that these people could help them get to information (like jobs? social events?) that a less connected user could not.

I was thinking about this as I was trying to explain network behavior to some students in class recently. Are users of Facebook aware of where they fall within their networks, meaning are they nodes themselves or far from the center of activity? If they are aware of this, does this change their behavior? Would it be beneficial for Facebook to show users where they fall in their network with the chance that it might boost their online activity levels?

The “friendship paradox” and the spread of disease

The social dimensions of diseases and medical conditions continue to draw research attention, particularly for those interested in mapping and understanding fast-spreading illnesses. A recent study, undertaken by a sociologist and medical geneticist/political scientist, explores how the flu spreads:

The persons at the center of a social network are exposed to diseases earlier than those at the margins states the paradox. Again, your friends are probably more popular than you are, and this “friendship paradox” may help predict the spread of infectious disease. However, Christakis and Fowler found that analyzing a social network and monitoring the health of members is an optimal way to predict a wave of influenza, detailed information simply doesn’t exist for most social groups, and producing it is time-consuming and expensive…

[Sociologist Nicholas] Christakis states: We think this may have significant implications for public health. Public health officials often track epidemics by following random samples of people or monitoring people after they get sick. But that approach only provides a snapshot of what’s currently happening. By simply asking members of the random group to name friends, and then tracking and comparing both groups, we can predict epidemics before they strike the population at large. This would allow an earlier, more vigorous, and more effective response.

This sounds like it has more promise than recently proposed techniques like monitoring Google searches or Twitter feeds.

Additionally, more and more research suggests that monitoring and analyzing social networks is critical for understanding the complex world. Rather than simply examining individuals, we now have some tools to map and model more complex social relationships.