LeterboxAnalysis

1. What question are you trying to answer?

   I am someone who hosts dinner for my friends every sunday. Along with dinner we tend to watch movies, and to be frank I am running out of movies to watch with them. Google movie recommendations are absolutely trash and I need to know why. I believe that there are biases in their search algorithm designed to find movie for the lowest common denominator.

2. Why is this question worth answering? This can be either because it has some personal value to you or because it is a question that others are asking. If it is a question others are asking, then provide an example.

   This is worth answering so whenever I look up the best comedy movies I can know why it recommends Grown Ups and Parasite. Hopefully narrowing down on their biases can help me direct my queries to produce better responses.

3. What is your hypothesis? Why leads you towards that hypothesis?

   My hypothesis is that google has a heavy bias towards certain studios and certain actors. I believe their search for the best movies has very little to do with the movies ratings and will be checking this against what the psychopaths at letterboxd have rated the movies.

4. What is the primary dataset(s) you will use to answer the question? The dataset(s) must be at least 15GB in their original form when downloaded. Provide links. You may not choose r/place (any year) as your analysis set.

   Kaggle Database Link

   DB size: 24.71GB