Most recently, Princeton researchers used epidemiological models to predict the rise and fall of Facebook. For these Princeton researchers, adoption and abandonment of an online social network such as Facebook was analogous to infection and recovery from a disease. By using findings from the world of epidemiology to model online social network popularity, they came to the conclusion that Facebook was doomed to lose 80 percent of its users by 2017. By 2021, Facebook may no longer exist as we know it.
But not so fast. As Facebook cheekily pointed out in response to the Princeton study, the same Google trends data used to predict the imminent demise of Facebook could just as easily be used to predict the imminent demise of Princeton. In one graph, Facebook playfully showed that Princeton would have only half of its student enrollment by 2018 — and no longer have any students by 2021. If you simply extrapolate from existing data, Facebook suggested, you could come to some startling conclusions about Princeton: “Based on our robust scientific analysis, future generations will only be able to imagine this now-rubble institution that once walked this earth.”
While the give-and-take between Princeton and Facebook is fun to debate, it actually points to a much bigger issue: How should we be thinking about online social networks in the digital age?
Ever since Malcolm Gladwell gave us The Tipping Point, we haven’t been able to shake our collective heads from the notion that any digital phenomenon should be viewed from within an epidemiological framework. As Gladwell suggested, any idea, trend or company could “spread like wildfire” once it reaches a tipping point. As a result, online social networks now race to add users by “infecting” them with an idea and then giving them multiple ways of sharing that idea with others. They attempt to “go viral” by creating certain types of connections between users. Instead of attempting to add users in a natural, organic manner – they look for sharp “spikes” in activity, the same way you might see a sharp spike in disease outbreaks in a certain geographic area.
The problem is that online social networks built to go viral instead of being “built to last” are ultimately fated to follow the unfortunate fate outlined by the Princeton researchers. You can question the validity of the data used by the Princeton researchers, and you can surely poke holes in some of their assumptions, but the basic argument makes sense: if a company is an epidemiological phenomenon, then it must undergo huge spikes in user popularity. It must reach a tipping point of user adoption and then fade away as users “recover” from the disease. For every Facebook, there’s a MySpace or Friendster.
Right now, it’s not apparent which online social network is ready to become “the next Twitter” or “the next Facebook.” However, it’s almost inevitable that we will see another multi-billion-dollar online social network after Facebook – the only question is what this social media company will look like. There are a number of different ideas out there. Maybe the next great online social network will exist solely on our mobile devices, and we won’t even think of it as an Internet company at all. Maybe the online social network will be connected by the Internet of Things, and we will form connections with millions of devices rather than hundreds of people.
One thing is clear, though. Silicon Valley needs to rethink its epidemiological approach to company building. With some notable exceptions — such as Evernote, which wants to become the first 100-year-old start-up — it seems that start-ups and entrepreneurs are too preoccupied with epidemiological approaches to building value. We’re all tired of being infected with new ideas, of being part of new viral marketing stunts, of having our “likes” transformed into advertising, of being constantly asked to empty out our address books to recruit new followers for the latest and greatest social media company. Yes, getting big still matters for new start-ups, but not at the expense of spreading “disease” throughout every corner of the Internet.