Network effects in social networking sites
This blog post analyzes data from the many social networks that have gained popularity recently in an effort to predict their future popularity. The battle between Facebook and Myspace is analyzed in terms of visitor data, as well as the recent progress of the three sites LinkedIn, Twitter, and Tumblr. Most relevant to what we’ve discussed in class is the author’s explanation of the recent fade in Facebook’s user growth. The recent month’s decline can be attributed to the fact that the because 73% of the U.S’s population already subscribes to facebook, the rest of the population has a very small value attributed to using facebook, and so naturally the rate of growth will decrease. It could be reasonably interpreted from the data that Facebook has neared its second equilibrium point where the reservation price of the last user equals the actual price in time of “facebooking”. This would explain the decline in user growth as a movement back towards stability. Fortunately for Facebook this does not necessarily mean total usage is declining, as the average user spends 1.7 hours per month more now than they did last year.
However on the opposite end of the success spectrum is Myspace, which has had both average user participation and number of users decrease significantly since Facebook rapidly gained popularity. This could be attributed to the raising of the comparative price of Myspace, as users can get more value from using Facebook instead, which changed the equilibrium so that Myspace no longer has the critical mass of users needed to sustain the social network. LinkedIn, Twitter and Tumblr are also examined, all three showing promising growth over the last year. LinkedIn has had the overall strongest showing, having grown 58% to 33.4 million visitors, vaulting it past Twitter. However, Tumblr has grown significantly as well, reaching its first 10 million visitor month in May of 2011. In fact the quickness of Tumblr’s climb indicates that it may have enough momentum to reach the critical mass, or first equilibrium point as we learned in class, to gain access to the majority of the market like Facebook has.
Although this blog post did not detail much about the actual mathematics of the various network effects at play it provided data and analysis that supports many of the ideas we’ve discussed in class. The author shows that these effects must be taken into account in order to accurately consider the valuations of large social networking companies.
Source: http://blog.comscore.com/2011/06/facebook_linkedin_twitter_tumblr.html