Thinking Of Facebook As A Disease

From an article in the (free) online maths magazine +plus:

If Facebook is a disease, then most of us know the symptoms: obsessive checking, a compulsion to share trivialities, and confusion about what’s real and what isn’t. But if Facebook is a disease, then why not use epidemiological methods to try and predict its future? This is what two scientists from Princeton University, New Jersey, have done. And they predict that Facebook is heading for a “rapid decline”: between 2015 and 2017 it will lose 80% of the users it had when it was at its peak in 2012…

Mathematical modelling is a tricky business, of course, because everything depends on the underlying assumptions. As the statistician George Box once said, “all models are wrong, but some are useful.” But Cannarella and Spechler did test the strength of their model on a social networking site that has already all but died out: MySpace. And they claim that it simulates MySpace’s life cycle well enough to validate the model. But if you try you could probably come up with plenty of arguments why Facebook and Myspace are two different kettle of fish, or other reasons why the model may not be valid…

Facebook responded (very quickly and amusingly) to the Princeton paper – see here:

In keeping with the scientific principle “correlation equals causation,” our research unequivocally demonstrated that Princeton may be in danger of disappearing entirely…

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.

Either way, and ignoring vested interests, it prompted some interesting thoughts!

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