PREDICTING LINKS IN SOCIAL NETWORKS: THE ISRAELI LAW SYSTEM and NETFLIX

A Bartal, Gilad Ravid

Research output: Contribution to journalArticlepeer-review

Abstract

A substantial foundation of the legal system is assigning judges randomly to a case, which makes it nearly impossible, to predict this pairing. A two mode social network, comprised of judges and lawyers, was build. We focused on the group of lawyers which appeared in front of a Supreme Court judge and in front of 255 different judges. One judge was randomly chosen, trying to predict the lawyers that will appear in front of him in the following years. Our results shows that some measures achieved significant performance in predicting new judge- lawyer interactions of 89.51%. The second experiment tried to predict viewers that will watch a certain movie in the future. The experiment was based upon Netflix data base, as a two mode network. We focused on the group of viewers who saw a certain movie. One movie was randomly chosen, tring to predict which of the viewers will see it. The model was able to achieve 95.27% of accuracy.
Original languageEnglish
JournalSunbelt-Social Networks Conference, Riva Del Garda Italy.
StatePublished - 2010

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