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Movie Rating Analysis

Danny Dean Webster University Data Mining Foundations, Fall 2009. Movie Rating Analysis. Outline. Data Set Research Description Analysis Technique Results. Data Set. Netflix Prize Data Set 17,000+ Movies 480,000+ Customers 100,000,000+ Ratings . Research Description.

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Movie Rating Analysis

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  1. Danny Dean Webster University Data Mining Foundations, Fall 2009 Movie Rating Analysis

  2. Outline • Data Set • Research Description • Analysis Technique • Results

  3. Data Set • Netflix Prize Data Set • 17,000+ Movies • 480,000+ Customers • 100,000,000+ Ratings

  4. Research Description • Can the number of words in a movie’s title be linked to its average rating?

  5. Analysis Technique • Collect a random sample of 1,537 movies • Group movies by the number of words in their title • “Paula Abdul's Get Up & Dance” = 6 words • Calculate the average rating for each group

  6. Results (1st Iteration)

  7. Results (2nd Iteration)

  8. Results (3rd Iteration)

  9. Comprehensive Results • Movies with 1, 2, or 3 words in their title consistently showed up at the bottom of the table with regard to average rating. • Movies with 4 or 5 words in their title maintained a position in the middle of the list (50th percentile) over each iteration. • Group of movies with 13 words in their title topped the charts over each iteration.

  10. Comprehensive Results (cont)

  11. Citations • McClave, S. (2009). A First Course in Statistics. Person Education, Inc. • Microsoft Corporation. (n.d.). MSDN. Retrieved December 05, 2009, from Random Class: http://msdn.microsoft.com/en-us/library/system.random(VS.71).aspx • UCI. (n.d.). UCI Machine Learning Repository. Retrieved December 12, 2009, from Netflix Prize Data Set: http://archive.ics.uci.edu/ml/datasets/Netflix+Prize

  12. Thank you! Questions?

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