Name: Letterboxd Movie Ratings Data
Creator: Kaggle
License: https://creativecommons.org/licenses/by/4.0/

About this Dataset

Letterboxd Movie Ratings Data

This is scraped, publicly accessible Letterboxd ratings data, taken from the top 4000 users on Letterboxd in any given month. and creates a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username. A user's "star" ratings are scraped from their Letterboxd profile and assigned numerical ratings from 1 to 10 (accounting for half stars). Movie data was enriched with data from the TMDB API.

The movie, user, and ratings tables here are exported from a Mongo database and each can be used to re-populate their respective collections in a local database for anyone who wants to build their own recommendations model/perform analysis without spending several hours re-scraping the data.

I put together a recommendation model for any Letterboxd user, based on this data which lives here: https://bit.ly/letterboxd-movie-recs

The Github repository for the crawler, recommendation model, and website, lives here: https://github.com/sdl60660/letterboxd_recommendations

Tables

Movie Data

@kaggle.samlearner_letterboxd_movie_ratings_data.movie_data

86.54 MB
285,963 rows
19 columns

CREATE TABLE movie_data (
  "n__id" VARCHAR  -- Id,
  "genres" VARCHAR,
  "image_url" VARCHAR,
  "imdb_id" VARCHAR,
  "imdb_link" VARCHAR,
  "movie_id" VARCHAR,
  "movie_title" VARCHAR,
  "original_language" VARCHAR,
  "overview" VARCHAR,
  "popularity" DOUBLE,
  "production_countries" VARCHAR,
  "release_date" TIMESTAMP,
  "runtime" DOUBLE,
  "spoken_languages" VARCHAR,
  "tmdb_id" DOUBLE,
  "tmdb_link" VARCHAR,
  "vote_average" DOUBLE,
  "vote_count" DOUBLE,
  "year_released" DOUBLE
);

Ratings Export

@kaggle.samlearner_letterboxd_movie_ratings_data.ratings_export

171.55 MB
11,078,167 rows
4 columns

CREATE TABLE ratings_export (
  "n__id" VARCHAR  -- Id,
  "movie_id" VARCHAR,
  "rating_val" BIGINT,
  "user_id" VARCHAR
);

Users Export

@kaggle.samlearner_letterboxd_movie_ratings_data.users_export

322.28 kB
8,139 rows
5 columns

CREATE TABLE users_export (
  "n__id" VARCHAR  -- Id,
  "display_name" VARCHAR,
  "num_ratings_pages" DOUBLE,
  "num_reviews" BIGINT,
  "username" VARCHAR
);