Baselight

IMDb Top Movie Characteristics And Reviews

Exploring Cinematic and Consumer Trends

@kaggle.thedevastator_imdb_top_250_movie_characteristics_and_reviews

About this Dataset

IMDb Top Movie Characteristics And Reviews


IMDb Top Movie Characteristics and Reviews

Exploring Cinematic and Consumer Trends

By [source]


About this dataset

This Kaggle dataset contains data related to the top movies according to IMDb, providing a unique insight into the trends and consumer reactions in the world of cinema over the years. With detailed columns listing out film names, scores, duration, release dates, countries of origin and language used as well as details on budgeted costs, gross revenue figures and collected reviews – both positive and negative – this is an exceptional resource for exploring the cinema world. To gain a deeper understanding of popular movie trends we can look into various genres featured in these movies or explore how particular countries have become renowned for certain film styles or sound types. Additionally, we can analyse user sentiments towards different movies reflected through their reviews - giving us a comprehensive overview of how each film has been received. With this dataset at our fingertips we now have access to information that will let us unlock intriguing discoveries about past cinema experiences as well as make better informed predictions about future ones!

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How to use the dataset

This dataset contains information about the top 250 movies according to IMDB. It includes columns such as name, score, genre(s), duration, release year, country of origin, language, sound format, color format in which the movie was filmed or presented onscreen or released and budget. Along with technical attributes the data also offers insight into user reviews on a six-point scale assigning positive ratings (good reviews) and negative ones (bad reviews).

Research Ideas

  • Predict the success of movie releases by analyzing features such as genre, budget, duration, and language for historical trends.
  • Visualize changes in consumer preferences for different genres of movies over time by comparing user reviews, budgets and ratings from year to year.
  • Utilize sentiment analysis on user reviews to understand what kinds of stories/themes cause certain reactions from viewers as well as create predictions on how a movie will be received upon release based on user feedback gathered before the movie has even come out

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: movies.csv

Column name Description
name The title of the movie. (String)
score The IMDb score of the movie. (Float)
genre1 The primary genre of the movie. (String)
genre2 The secondary genre of the movie. (String)
genre3 The tertiary genre of the movie. (String)
duration The length of the movie in minutes. (Integer)
release The year the movie was released. (Integer)
rating The MPAA rating of the movie. (String)
country The country of origin of the movie. (String)
language The language of the movie. (String)
sound The sound format of the movie. (String)
color The color format of the movie. (String)
budget The budget of the movie in USD. (Integer)
gross The total gross of the movie in USD. (Integer)
badReviews The number of bad reviews for the movie. (Integer)
neutralReviews The number of neutral reviews for the movie. (Integer)
goodReviews The number of good reviews for the movie. (Integer)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Movies

@kaggle.thedevastator_imdb_top_250_movie_characteristics_and_reviews.movies
  • 29.53 KB
  • 250 rows
  • 18 columns
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CREATE TABLE movies (
  "name" VARCHAR,
  "score" DOUBLE,
  "genre1" VARCHAR,
  "genre2" VARCHAR,
  "genre3" VARCHAR,
  "duration" BIGINT,
  "release" VARCHAR,
  "rating" VARCHAR,
  "country" VARCHAR,
  "language" VARCHAR,
  "sound" VARCHAR,
  "color" VARCHAR,
  "ratio" VARCHAR,
  "budget" VARCHAR,
  "gross" VARCHAR,
  "badreviews" BIGINT,
  "neutralreviews" BIGINT,
  "goodreviews" BIGINT
);