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Analyzing and Predicting Triadic Closure in Social Networks

https://ieeexplore.ieee.org/document/7152900

 

In this study the authors set out to research what are the key sources to triadic closure.  The authors argue that understanding what causes triadic closure will allow social network providers to encourage triadic closure creating a larger and more profitable user base who remain active and encourage new members.  The authors used the social network Weibo to gather data and create a statistical prediction model for how triadic closure occurs. Some results from the study that I found interesting are listed here:

  • Males are 6x more likely to form a triad as opposed to females.
  • Celebrity users (users with a high traffic page) are 421x more likely to form a triad as opposed to average users.
  • Users who interacted on some level are 3x more likely to form a triad as opposed to 3 users who have never interacted.
  • The formation of a triad is typically done by the last person to join the network unless they are a Celebrity user.

As discussed in lecture a triangle is one of the most basic shapes in a network and as we can see from the study that understanding how Triadic Closure occurs in networks may have monetary results and gives us a different view on how connections are made.

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