Oscar Award Nominees And Winners by Kaggle | Other

About this Dataset

Oscar Award Nominees And Winners

Oscar Award Nominees and Winners

Uncover Historical Insights and Trends in the Film Industry

About this dataset

This dataset features a collection of award-winning and Oscar-nominated films from 1929 to the present, giving an invaluable understanding into the historical trends within these prestigious film awards. It contains information regarding the titles, original titles, year of release, duration, country of release, director, actors, genre and other essential aspects of each selected movie. Furthermore it also details the awards received by each movie as well as ratings on average given by audiences around the world. Each movie poster is also included to help give you a better understanding behind some of these great cinematic masterpieces. With data that includes rating votes and user vote for movies nominated for this iconic prize; this dataset will enable researchers to identify patterns and correlations amongst some of the greatest motion pictures ever made - allowing us all to explore how these cultural phenomena have developed over almost a century!

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How to use the dataset

This dataset provides valuable insights into the winners, nominees and trends of the best movie Oscar award since its inception in 1929. In order to get started in analyzing the data, it is important to understand each of the columns provided and how they can be used together to uncover trends or other patterns.
Each row contains information associated with a particular movie: title, original title, year of release, duration, country of release, director, actors, genre given as strings; description given as plain text; awards received (if any) along with floats representing ratings (average rating and number of rating votes) related metrics. Further analysis can be done using reviews gathered from major sources like IMDB or Rotten Tomatoes as well as posters related to movies. Ultimately reviews can provide a deeper level understanding regarding viewers responses while posters helps us gain further insights on production values at this time-period. For example user’s own vote can be assembled from online voting sites by utilizing higher-level language processing techniques such as sentiment analysis for gauging positive/negative reactions towards nominated films which cannot otherwise looked upon through average votes alone.

Research Ideas

Analyzing the impact of drama films compared to other genres in terms of winning the Oscar award - By delving into differences this data provides between the nominated movies and Oscars winners, it is possible to identify trends and explore the success rate of certain genres. This can be done by creating a comparison between dramatic films, fantasy films, comedies, war films etc.

Measuring influential directors throughout history - By looking at each director's won awards for their movie nominations over time we can measure which ones have been particularly influential in advancing technology or techniques used in filmmaking to win awards and differentiate between those who have had consistent success with different storytelling approaches compared to those who use more traditional methods that were groundbreaking during their time.

Tracking what awards or honors a particular actor is associated with throughout their career- By searching through this dataset by an actor name one can easily track down what sort of honor an individual has achieved not only within movies but across fields such as television series where certain actors may achieved popularity but less recognition with respect to awards

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: movie_data.csv

Column name	Description
title	The title of the movie. (String)
original_title	The original language title of the movie. (String)
year	The year the movie was released. (Integer)
duration	The length of the movie. (Integer)
country	The country of release. (String)
director	The director of the movie. (String)
actors	The actors starring in the movie. (String)
genre	The genre categorization of the movie. (String)
description	A description providing insight into the plot, characters, etc. (String)
awards	Awards won by the movie. (String)
average_rating	The average rating provided by users on IMBD/Rotten Tomatoes/etc. (Float)
rating_votes	The number of rating votes for the movie on IMBD/Rotten Tomatoes/etc. (Integer)
reviews	User reviews for the movie. (String)
poster	Poster images showcasing artwork used to advertise the movie. (Image)
my_vote	User's own personal vote given to each nominated film based off watching them or viewing their trailer. (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

Movie Data

@kaggle.thedevastator_oscar_award_nominees_and_winners_1929_2020_movie.movie_data

402.04 KB
563 rows
17 columns


CREATE TABLE movie_data (
  "unnamed_0" BIGINT,
  "id_fa" BIGINT,
  "title" VARCHAR,
  "original_title" VARCHAR,
  "year" BIGINT,
  "duration" VARCHAR,
  "country" VARCHAR,
  "director" VARCHAR,
  "actors" VARCHAR,
  "genre" VARCHAR,
  "description" VARCHAR,
  "awards" VARCHAR,
  "average_rating" DOUBLE,
  "rating_votes" DOUBLE,
  "reviews" DOUBLE,
  "poster" VARCHAR,
  "my_vote" DOUBLE
);