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Authors : Cristian Danescu-Niculescu-Mizil (Cornell University, NY, USA) Gueorgi Kossinets (Google Inc., Mountain View, CA, USA) Jon Kleinberg (Cornell University, NY, USA) Lillian Lee (Cornell University, NY, USA)
Abstract ,[object Object],[object Object],[object Object],[object Object]
Introduction ,[object Object],[object Object],[object Object],[object Object]
Data ,[object Object],[object Object],[object Object],[object Object]
Important Terms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Helpfulness Votes Star Rating of Reviews Average Star Rating by Amazon
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
Theories underlying Helpfulness Evaluation ,[object Object],[object Object],[object Object],[object Object]
Conformity Hypothesis ,[object Object],[object Object],[object Object]
Fig 1: Helpfulness ratio declines with the absolute value of a review’s deviation from the computed star average; this behavior is predicted by the conformity hypothesis The line segments within the bars (connected by the descending line) indicate the median helpfulness ratio; the bars depict the helpfulness ratio.
Fig 2: The dependence of helpfulness ratio on a review’s signed deviation from average is inconsistent with both the brilliant-but-cruel and, because of the asymmetry, the conformity hypothesis.
[object Object],[object Object],[object Object]
Brilliant-but-cruel Hypothesis ,[object Object],[object Object],[object Object],[object Object]
Individual-Bias Hypothesis ,[object Object],[object Object],[object Object],[object Object],[object Object]
Figure 3: As the variance increases, the median helpfulness ratio curve becomes two-humped and the helpfulness ratio at signed deviation 0 (indicated in red) no longer represents the unique global maximum. There are non-zero signed deviations in the plot for variance 0 because we rounded variance values to the nearest .5 increment.
Controlling for Text Quality ,[object Object],[object Object],[object Object],[object Object],[object Object]
Key Insights  ,[object Object],[object Object]
Identifying Plagiarism ,[object Object],[object Object],[object Object]
Conclusion for text Quality ,[object Object],[object Object],[object Object]
Model based on Individual bias and Mixtures of Distributions ,[object Object],[object Object],[object Object],[object Object]
Consistency among Countries ,[object Object],[object Object]
Conclusion ,[object Object],[object Object]
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Artificial Intelligence

  • 1. Authors : Cristian Danescu-Niculescu-Mizil (Cornell University, NY, USA) Gueorgi Kossinets (Google Inc., Mountain View, CA, USA) Jon Kleinberg (Cornell University, NY, USA) Lillian Lee (Cornell University, NY, USA)
  • 2.
  • 3.
  • 4.
  • 5.
  • 6. Helpfulness Votes Star Rating of Reviews Average Star Rating by Amazon
  • 7.
  • 8.
  • 9.
  • 10.
  • 11. Fig 1: Helpfulness ratio declines with the absolute value of a review’s deviation from the computed star average; this behavior is predicted by the conformity hypothesis The line segments within the bars (connected by the descending line) indicate the median helpfulness ratio; the bars depict the helpfulness ratio.
  • 12. Fig 2: The dependence of helpfulness ratio on a review’s signed deviation from average is inconsistent with both the brilliant-but-cruel and, because of the asymmetry, the conformity hypothesis.
  • 13.
  • 14.
  • 15.
  • 16. Figure 3: As the variance increases, the median helpfulness ratio curve becomes two-humped and the helpfulness ratio at signed deviation 0 (indicated in red) no longer represents the unique global maximum. There are non-zero signed deviations in the plot for variance 0 because we rounded variance values to the nearest .5 increment.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.