STUDY: Facebook May Lose 80% Of User Base Between 2015 And 2017

Facebook is already experiencing some erosion in usage, but will the social network see 80 percent of its user base disappear between 2015 and 2017? Possibly, according to a new study by researchers from Princeton University, which compared the life cycles of ideas with the life cycles of diseases. The researchers believe that if their findings are correct, Facebook users will lose interest in the social network as their peers do, with the bulk of this activity occurring between 2015 and 2017. The reasoning behind the study follows: In this paper, we analyze the adoption and abandonment dynamics of online social networks by drawing analogy to the dynamics that govern the spread of infectious disease. The application of disease-like dynamics to OSN adoption follows intuitively, since users typically join OSNs because their friends have already joined. The precedent for applying epidemiological models to non-disease applications has previously been set by research focused on modeling the spread of less-tangible applications such as ideas. Ideas, like diseases, have been shown to spread infectiously between people before eventually dying out, and have been successfully described with epidemiological models. Again, this follows intuitively, as ideas are spread through communicative contact between different people who share ideas with each other. Idea manifesters ultimately lose interest with the idea and no longer manifest the idea, which can be thought of as the gain of “immunity” to the idea. While the traditional SIR model captures the infectious uptake dynamics of OSNs, the assumption of a characteristic recovery rate in the traditional SIR model is of doubtful validity for modeling the abandonment of OSNs. Contrary to the SIR model’s assumption of a characteristic recovery rate for diseases, OSN users do not join an OSN expecting to leave after a predetermined amount of time. Instead, every user that joins the network expects to stay indefinitely, but ultimately loses interest as their peers begin to lose interest. Thus, a user that joins early on is expected to stay on the network longer than a user that joins later. Eventually, users begin to leave and recovery spreads infectiously as users begin to lose interest in the social network. The notion of infectious abandonment is supported by work analyzing user churn in mobile networks, which show that users are more likely to leave the network if their contacts have left. Therefore, it is necessary to modify the traditional SIR model to include infectious recovery dynamics, which intuitively provide a better description of OSN abandonment. And looking at Facebook specifically, the researchers concluded: In this paper, we have applied a modified epidemiological model to describe the adoption and abandonment dynamics of user activity of online social networks. Using publicly available Google data for search query MySpace as a case study, we showed that the traditional SIR model for modeling disease dynamics provides a poor description of the data. A 75 percent decrease in SSE is achieved by modifying the traditional SIR model to incorporate infectious recovery dynamics, which is a better description of OSN dynamics. Having validated the irSIR model of OSN dynamics on Google data for search query MySpace, we then applied the model to the Google data for search query Facebook. Extrapolating the best fit model into the future suggests that Facebook will undergo a rapid decline in the coming years, losing 80 percent of its peak user base between 2015 and 2017. Readers: What did you think of the findings by the researchers from Princeton? Images courtesy of Shutterstock.

Social Pro Daily

STUDY: Facebook May Lose 80% Of User Base Between 2015 And 2017

Facebook is already experiencing some erosion in usage, but will the social network see 80 percent of its user base disappear between 2015 and 2017? Possibly, according to a new study by researchers from Princeton University, which compared the life cycles of ideas with the life cycles of diseases.

David Cohen

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David Cohen