Princeton's suspicions about Facebook aren't absurd

date
Jan 23, 2014
slug
2014-princetons-suspicions-about-facebook-arent-absurd
status
Published
tags
richness
users
information
networks
Facebook
summary
Princeton study predicts decline in Facebook's user base using mathematical models similar to contagious diseases, raising questions about the future of mass social platforms.
type
Post
Two researchers from Princeton University stirred up some controversy this week by publishing a study (pdf) that predicts an 80% drop in Facebook's user base within a short period (between one and three years). Mark Zuckerberg's social network made fun of the research in a good-humored way, suggesting that Princeton would no longer have any students by 2021. However, the study raises an interesting idea. Even if the prediction seems too catastrophic (for Facebook, of course), it carries indicators that point to a future that is more niche and hyper-connected than mass and closed platforms.
The study (which is interesting to read, even for laymen) essentially compares the evolution of the user base to mathematical models similar to those that explain the spread of highly contagious diseases, like bubonic fever, for example. According to the researchers, the models not only served to explain the spread of Facebook but also fit when applied to the downward curve of MySpace, a social network that imploded after its purchase by News Corporation.
But what does a social network have to do with an infectious disease? Well, possible jokes aside, according to the study, the same mathematical models that work when applied to the evolution curves of epidemics, serve to track the way an idea spreads. Also, according to the research, in the case of ideas, a certain population stops adhering to a specific thought after a certain stage of the "infection", whose equivalence in the case of disease would be the "immunization" that prevents the population from being extinct.
The good humor of Facebook's note argues that not every application of mathematical models serves for anything - which is true. But it is quite curious that some numerical projections repeat themselves in situations as different as the evolution of bubonic fever and the growth of a social network. And as mathematics is the most universal language of all, regardless of its accuracy, perhaps the study will be useful for broader projections.
Social networks are, par excellence, virtual communities that unite people with similar interests. They basically flourish for one reason - to promote the exchange of information between individuals and/or associations, companies, entities, etc. Let's say that the circulatory system of a social network is the amount of information it moves. Using the same allegory, obstructions in this circulation tend to be harmful to its functioning as a whole.
However, in practice, social networks are not managed as living organisms, as the allegory suggests. They are businesses, whose sole objective (in the vast majority of cases) is to make money. Regardless of how harmful these interventions in search of more revenue may be to the healthy functioning of the network in the long run, nothing matters beyond presenting profits to shareholders (from the Aesop's fable of the Goose that Laid the Golden Eggs to the movie The Corporation, not even the logic that the danger of death dampens greed serves to change the human vocation to prioritize short-term results).
The nature of the agglutination of people around interests, however, does not recognize the need for shareholders to make money. People join social networks because they gain from them - information, satisfaction, new contacts, professional advantages. Once these interests are overlapped by others, the social network loosens its bond.
Not only Facebook, but all social networks, follow paths against the current, in terms of both observing common interest and exchanging information. These services treat the information collected by users with utmost secrecy, sometimes even prohibiting measurement tools like ComScore from evaluating certain types of data. This is something obvious in the current business model: the gold of the goose here are not the users, but the data they provide in exchange for the service. And strictly speaking, damn any other type of consideration that goes against this reasoning.
The digital medium did not come to eliminate mass communication media, but it will undoubtedly force them to play another game. Using another allegory, it's like cable TV, which shoves useless channels down our throats. In this new scenario, cable TVs will disappear, because we will no longer accept what is being offered. The logic will be reversed, for better or worse, with more or less sacrifice and the offer will have to be of what we want. And the more these platforms accept to connect to others, the more advantages they will have, especially because this type of opening to external information will force them to be in constant evolution - coincidence or not, another similarity with observations of the natural world.
The temptation to open the goose and take all the gold at once, however, is too great since Aesop was a baby. Princeton's prediction for Facebook sounds a bit radical, but probably carries material for reflection - especially since it's no secret that Facebook is losing momentum with younger users, who prefer platforms like Snapchat. Social networks and all other operations aimed at profit will not stop applying their business models and marketing strategies because of a theoretical risk. The dose of accuracy of Princeton's study will be clarified by time - with the collaboration of Facebook that can - or may not - take the warning into account.

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