Facebook may be headed toward the same unhappy fate as its predecessors, Friendster and MySpace, according to a provocative new study from researchers at Princeton’s Department of Mechanical and
Aerospace Engineering, who predict that Facebook will lose 80% of its user base by 2017.
Sound crazy? Maybe, maybe not.
The study, titled “Epidemiological Modeling
of Online Social Network Dynamics,” which has not been peer reviewed, applies statistical techniques for the study of contagious diseases to social networks. The model basically treats an online
social network like Facebook as a disease that spreads between individuals: an individual is “infected” (becomes a user) after exposure to a certain number of other “infected”
people, meaning people who are already using the site.
The same principle is then applied, in reverse, to the “recovery” phase: Someone who is using the social network
will “recover” (stop using the network) after exposure to a certain number of other non-users, including people who stopped using the network or never joined in the first place.
The researchers draw their data from Google Trend search query data to provide a measure of the level of Web traffic for a given online social network, focusing on active users rather than mere
registered (possibly inactive) users.
This model resembles one proposed in a previous study, “Social Resilience in Online Communities: The Autopsy of Friendster,” which
identified a “cascade” phenomenon in both the growth and decline of social networks. Similarly, in that model, the probability that an individual will stop using a social network increases
with the number of people they know who have left that social network. Both models suggest that the rate of decline can accelerate very quickly once users begin abandoning the social network, leading
to a snowball effect finally resulting in mass desertion.
There are a few obvious issues about using the infectious disease model to analyze online social networks, which the
researchers readily admit they do not address. For example, while recovery from a disease is a biological phenomenon, the decision to leave a social network is social-psychological. That raises the
question of what sets the process in motion: The first individuals to recover from a disease do so as a natural function of their immune systems, but why do the first users choose to abandon the
(As the researchers point out, the model also requires a small “initially recovered” population, meaning a group that never converted in the first place,
otherwise, there would be no possibility of general recovery).
Nonetheless, assuming the basic approach is valid, the implications are clear, according to the researchers, who believe
“the search query data suggests that Facebook has already reached the peak of its popularity and has entered a decline phase, as evidenced by the downward trend in search frequency after
Looking ahead, “Extrapolating the best fit into the future shows that Facebook is expected to undergo rapid decline in the upcoming years, shrinking to 20% of its
maximum size by December 2014,” and eventually “losing 80% of its peak user base between 2015 and 2017.”