Debunking Princeton and Facebook’s imminent demise with hilarity

Princeton University recently released a study, which predicted that by 2017 Facebook would lose 80% of its current user base. The clever folks at the University’s Department of Mechanical and Aerospace Engineering presented what they probably thought was a well thought-out argument with some solid science and mathematical calculations to go with it.

Princeton’s methodology likens the social a network to an “infectious disease” its users will soon “recover” from. The methodology they speak of: Google search data.

“Having validated the application of the irSIR model to the adoption dynamics of OSNs, we now apply the irSIR model to the Google search query data for Facebook,” says the report.

After some of that querying and graphing the group came up with this:

Extrapolating the best fit model into the future suggests that Facebook will undergo a rapid decline in the coming years, losing 80% of its peak user base between 2015 and 2017

You can imagine the issues a report like this must have caused over at one Hacker Way. Research like this does not bode well for a listed company hoping for higher share prices. So Facebook’s own data scientists (Mike Devlin, Lada Adamic, and Sean Taylor) thought they would give Princeton’s “robust methodology” a test by predicting the institution’s own imminent demise.

The result is quite hilarious and teaches Princeton a thing or two about relying too much on future thought.

Below is Facebook’s study:

Like many of you, we were intrigued by a recent article by Princeton researchers predicting the imminent demise of Facebook. Of particular interest was the innovative use of Google search data to predict engagement trends, instead of studying the actual engagement trends. Using the same robust methodology featured in the paper, we attempted to find out more about this “Princeton University” – and you won’t believe what we found!

In keeping with the scientific principle “correlation equals causation,” our research unequivocally demonstrated that Princeton may be in danger of disappearing entirely. Looking at page likes on Facebook, we find the following alarming trend:

Now, Facebook isn’t the only repository of human knowledge out there. A search of Google Scholar revealing a plethora of scholarly articles of great scholarliness turned up the following results, showing the percentage of articles matching the query “Princeton” by year:

The trend is similarly alarming: since 2009, the percentage of “Princeton” papers in journals has dropped dramatically.

Of course, Princeton University is primarily an institution of higher learning – so as long as it has students, it’ll be fine. Unfortunately, in investigating this, we found a strong correlation between the undergraduate enrollment of an institution and its Google Trends index:

Sadly, this spells bad news for this Princeton entity, whose Google Trends search scores have been declining for the last several years:

This trend suggests that Princeton will have only half its current enrollment by 2018, and by 2021 it will have no students at all, agreeing with the previous graph of scholarly scholarliness. Based on our robust scientific analysis, future generations will only be able to imagine this now-rubble institution that once walked this earth.

While we are concerned for Princeton University, we are even more concerned about the fate of the planet — Google Trends for “air” have also been declining steadily, and our projections show that by the year 2060 there will be no air left:

As previous researchers [J. Sparks, 2008] have expressed in the past, this will have grievous consequences for the fate of all humanity, not just our academic colleagues in New Jersey.

Although this research has not yet been peer-reviewed, every Like for this post counts as a peer review. Start reviewing!

P.S. We don’t really think Princeton or the world’s air supply is going anywhere soon. We love Princeton (and air). As data scientists, we wanted to give a fun reminder that not all research is created equal – and some methods of analysis lead to pretty crazy conclusions.