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Facebook Report Brings the World Closer Together

Wolfram alpha recently launched a new tool known as “facebook report” which generates a surprisingly large set of personal analytics for a given facebook user. Such analytics include: analysis of activity, such as when one posts status updates, analysis of friends, such as producing a pie chart containing the relationship status of friends, and a graph of your social network as seen by facebook.


An article about the facebook report tool can be found here:


In my opinion, the most interesting thing about the facebook report is the friendship network that it outputs – a graph containing all of one’s friends along with the friendships between them. To me it was quite interesting to see how my friends connected to one another and what clusters they formed.


This clearly connects to the part of class where we were talking about information passing through a social network via strong or weak ties, although in class, we assumed that we were unaware of the ties between our friends, and had to guess the strength of second degree connections based on our own first degree connections. With this facebook report graph, however, I can see which of my friends are connected to which other friends, and thus infer more about the strength of various ties and, in doing so, figure out who might be the best person to talk to about a potential job lead, for example (someone I’m weakly tied to, which on my graph would appear as an isolated or weakly connected region of nodes).


Thus, the facebook report can effectively be used as a tool to find the weak links between clusters of people and strengthen them, thus, effectively making for a closer knit community. This idea is confirmed by a study published by facebook in 2011 ( The study revealed that “users tend to view more information from “friends” they don’t interact with much in real life than those they do,” thus further validating the idea that social networking sites have the effect of bringing together people that would otherwise remain separated, thus resulting in bigger close knit communities and therefore, faster transmission of information, as there are less weak links that it must travel through.



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