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Network Effects: Facebook

Facebook has become a “power-house” when it comes to running the show on the social media forefront.  It’s number of users far surpasses any of its counterparts or those who may be trying to overtake its place in the type of website.  How exactly did this come to be?  Why did it happen?  What occurred was a network effect; more specifically, the threshold rule comes into play.  As is widely known, it was created by Mark Zuckerberg and accordingly had its beginning at Harvard.  From there, it spread among the students and to other ivy league universities.  Once said students graduate and got jobs, it would then spread to their coworkers and etc.  Why did this type of spread happen?  It is due to the social networks that people are a part of.  If people see that their friends are beginning to use this item, they too will begin to use it; however, it depends on the payoff of said item.  Say for example there are two potential websites, the user’s true payoff depends upon how many of his/her friends are using the website AND the specific value the user gets for choosing said site (ex. site A has value a and site B has value b).

What the article mentions, which is quite interesting, is that the actual number of friends who use the site is not as important in determining the payoff; thus, it is not as important in regards to the threshold rule and determining the whether or not the user should join the site.  Professor Kleinberg was even quoted in the article saying, “What jumped out at us was that someone’s likelihood of joining really corresponded not to the number of friends represented, but to how many disconnected groups the friends listed on the e-mail fell into,”.  What this means is that it really isn’t the number of friends, but the potential exposure to different networks and different groups of people that seems to draw people into using the site.  They may see people from different sectors of the work force, from different states, of different ethnicites, or many other possibilities, and this seems to cause them to join more often than simply seeing friends they know.  This could be due to the fact that they already have a connection with these friends and don’t see a need to create another, but it truly is open to interpretation.  Going back to the example given earlier, is this factor, as a whole, shown in the values of a and b, or is it unaccounted for?  In that case, is the threshold rule as valid as we believe it to be?

 

Source:

http://news.sciencemag.org/2012/04/how-facebook-contagion-spreads

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