movies and TV shows

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FilmTV movies dataset

FilmTV movies dataset

Stefan
Open Dataset
Creators: (Leone, Stefano)
Publication Date: 2018
Creators: (Leone, Stefano)

The FilmTV movies dataset serves as a valuable resource for researchers, data analysts, and movie enthusiasts interested in exploring various aspects of cinema. With data spanning over a century, the dataset provides a broad temporal view of film trends, genre popularity, and audience reception. Movies data are available on websites such as IMDb with average votes, vote numbers, reviews and descriptions. While IMDb is the most trustworthy source for data, other websites as FilmTV can provide the information on how users from different countries rate the movies compared to each other. The dataset is 0.11 GB large.

Each row represents a movie available on FilmTV.it, with the original title, year, genre, duration, country, director, actors, average vote and votes.
The file in the English version contains 37,711 movies and 19 attributes, while the Italian version contains one extra-attribute for the local title used when the movie was published in Italy.

The data set includes movies from: 1897 – 2023. Data has been scraped from the publicly available website https://www.filmtv.it as of 2023-10-21.

Rotten Tomatoes movies and critic reviews dataset

Rotten Tomatoes movies and critic reviews dataset

Stefan
Open Dataset
Creators: (Leone, Stefano)
Publication Date: 2020
Creators: (Leone, Stefano)

The Rotten Tomatoes Movies and Critic Reviews dataset is a collection of information scraped from the Rotten Tomatoes website as of October 31, 2020. It encompasses data on over 17,000 movies, including details such as movie titles, descriptions, genres, durations, directors, actors, as well as user and critic ratings. A distinctive feature of this dataset is its ability to facilitate comparisons between audience scores (ratings from regular users) and tomatometer scores (ratings from certified critics), offering valuable insights into differing perspectives on films. In the movies dataset each record represents a movie available on Rotten Tomatoes, with the URL used for the scraping, movie tile, description, genres, duration, director, actors, users’ ratings, and critics’ ratings.
In the critics dataset each record represents a critic review published on Rotten Tomatoes, with the URL used for the scraping, critic name, review publication, date, score, and content.

Rotten Tomatoes allows to compare the ratings given by regular users (audience score) and the ratings given/reviews provided by critics (tomatometer) who are certified members of various writing guilds or film critic-associations.The dataset is 0.23 GB large.

The dataset is structured into two main components:

  1. Movies Dataset: Each record represents a movie available on Rotten Tomatoes, containing fields such as:

    • rotten_tomatoes_link: The specific URL from which the movie data was scraped.
    • movie_title: The title of the movie as displayed on the Rotten Tomatoes website.
    • movie_info: A brief description of the movie.
    • genres: The genres associated with the movie, separated by commas if multiple.
    • original_release_date: The date on which the movie was originally released.
    • content_rating: The category indicating the movie’s suitability for different audiences.
    • critics_consensus: Comments from Rotten Tomatoes summarizing critics’ opinions.

  2. Critics Dataset: Each record represents a critic’s review published on Rotten Tomatoes, including details such as:

    • critic_name: The name of the critic who reviewed the movie.
    • top_critic: A boolean value indicating whether the critic is classified as a top critic.
    • publisher_name: The name of the publication for which the critic works.
    • review_type: Specifies whether the review was labeled as ‘fresh’ or ‘rotten’.
    • review_score: The score provided by the critic for the movie.
    • review_date: The date when the review was published.
    • review_content: The content of the review.
Web data: Amazon movie reviews

Web data: Amazon movie reviews

Stefan
Open Dataset
Creators: McAuley, Julian; Leskovec, Jure
Publication Date: 2012
Creators: McAuley, Julian; Leskovec, Jure

This dataset is a collection of approximately 8 million movie reviews from Amazon, spanning over a decade up to October 2012. It is particularly valuable for analyzing consumer behavior, sentiment analysis, and the evolution of user expertise in online reviews. In total, the dataset has a size of 3,1 GB. Each review includes detailed information such as the product’s unique identifier (ASIN), user ID, profile name, helpfulness rating, score, time of review (in Unix time), summary, and the full text of the review.

The dataset is organized with each review capturing multiple attributes:​

  • Product Information: Including the product’s unique identifier (ASIN).​

  • User Information: Such as user ID and profile name.​

  • Review Details: Encompassing helpfulness rating, score, time of review, summary, and the full text.

 

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