Facebook derides Princeton’s research, says Princeton in danger of disappearing entirely

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Taking on hard at Princeton’s research that quoted Facebook will loose 80% of its users by 2015-2017, Facebook’s Data Scientist Mike Develin and his colleagues Lada Adamic and Sean Taylor debunked Princeton saying the university may be in danger of disappearing entirely.

Princeton vs Facebook

Princeton University’s researchers carried out a wide study and concluded that Facebook may loose 80% of its users by 2015-1017. The conclusion was based on epidemiological modelling of online social network dynamics. The research paper quoted that the adoption of any online social network is analogous to infection and its abandonment is analogous to recovery. It is like saying that Facebook is a ‘disease’ and people will soon ‘recover’ from it. The research is done using Google’s search query data which shows a massive decline in search query ‘Facebook’.

Facebook derided the research calling is a nonsense.  In its starting phase, Facebook was searched a lot over the internet. Queries like ‘Facebook’ and ‘Facebook Login’ were searched by millions. However, after some time when Facebook did become popular, it is but natural for the ‘Facebook’ search statistics to decline. Also a large number of people use Facebook through its app, which is in fact a major factor for this plummet.

Facebook’s Data Scientist Mike Develin with his colleagues in keeping with the scientific principle ‘correlation equals causation’ demonstrated that Princeton may be in danger of disappearing entirely. They analysed various trends to piggyback this conclusion. The number of likes on Princeton’s Facebook page, the number of articles that turned up in Google matching the query ‘Princeton’ and the Google Trends search scores revealed a decline in Princeton’s popularity. Going by the trends, Princeton will have half the number of students in 2018 and none at all by 2021.

Read the full Debunking Princeton article by Mike Develin here.

Read the Princeton’s Epidemiological Modelling of Online Social Network Dynamics here.

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