CS506_FinalProject

Analysis on Features that Contribute to the Success of a Movie

Datasets:

• IMDB Movie Dataset: https://www.kaggle.com/orgesleka/imdbmovies

• MovieLens 1M Dataset: https://grouplens.org/datasets/movielens/

• 350000+ movies from themoviedb.org: www.themoviedb.org

• MovieLens 100K: https://grouplens.org/datasets/movielens/

Questions:

• Q1: Which important features (e.g. genres, age of users, sex of users, occupation of users, etc.) influence the IMDB score the most?

• Q2: Are there differences in movies' ratings by occupations?

• Q3: Do the type of movies the users watched predict the users' gender?

• Q4: Can we predict this year's biggest box office hits in the theaters with mostly "inherent" movie characteristics?

• Q5: How well can we predict if a person might enjoy a certain type of movie based on the movies he has already watched and the ratings of such movies?

• Chuan Xing Zheng ([czheng78@bu.edu])
• Zexu Chai ([chaizexu@bu.edu])
• Chenyu Wang ([wangcy@bu.edu])