In 2025, men almost accounted for the majority of the nominees for all major non-acting categories at the Academy Awards. All contenders in the Cinematography category were male. The category with the highest level of female participation that year was Documentary (short subject).

Oscar-Winning Directors Analysis

Examining Gender, Race and Director Trends from 1930-2019

By Priyanka Dobhal [source]

About this dataset

This dataset collects information on the Academy Award for Best Director winners from 1930 to 2019, and provides insight into the gender and racial disparity of filmmaking over time. It includes the winner's name, their respective award year, race, gender, nominated/winning film title, and the filmmakers' names. By looking at this data it is possible to identify emerging trends in cinema- such as who is dominating in terms of awards recognition- and consider how much progress has been made when it comes to equal opportunity within Hollywood. Examining Oscar winning directors over time can tell us a lot about its impact on systemic issues in our society as diversity increases among winners. To deepen our understanding of this award’s significance it is necessary to consider all factors included; from awarded directors’ gender to what kind of films are being supported by these awards annually. So come explore with us! Let's take an analysis deep dive into almost nine decades worth of cinematic history - starting from 1930 - and see who won big at the Academy Awards…

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How to use the dataset

This dataset is the perfect resource for anyone looking to conduct an analysis of the Academy Award for Best Director winners from 1930 to 2019. It contains information on the year, gender, race, director(s), film and nomination/winner of each winner.

By using this dataset, you can gain insight into trends in Oscar winning directors over time. For example, you can compare the number of nominees between different years or examine differences in representation of gender and race among directors who have won Oscars over time. Additionally, you can use this data to explore the films that have received an Oscar for best director – which films were most successful from a narrative perspective? Or analyze which films used unique filming techniques or visual designs? Finally, this dataset also makes it possible to conduct more targeted analyses by identifying patterns across multiple aspects such as furthering social issues that are depicted in film through positive filmmaking - such as LGBTQ representation.

To start exploring with this dataset:

2) Open your favorite spreadsheet program ('Microsoft Excel', 'Libre Office', etc.)

3) Load csv file with' File —> Open' command

4) Review column headers and values contained within each row

5) Start creating charts and graphs (pie charts barplots etc.) that show trends over time according to your needs

6) Take notes while analyzing datasets

7) Publish your findings online if desired

The possibilities are endless! If you’d like additional guidance or tips on how to effectively use this data set please subscribe our newsletter at oscarwinningdirectorsanalysisgmail.com

Research Ideas

• Analyzing gender and racial disparity in the Academy award for Best Director across different years.
• Investigating if the age of directors has an effect on what film they create and how successful it is at winning an Oscar for Best Director.
• Crafting a recommendation system to recommend movies based on a director's previous Oscar-winning work or even pair users with film recommendations that have similar director/genre preference in order to discover new titles they may enjoy watching

Acknowledgements

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

License

See the dataset description for more information.

Columns

File: Oscar Winners - Director.csv | Column name | Description | |:----------------------|:--------------------------------------------------------------| | Year | The year in which the award was given. (Integer) | | Gender | The gender of the director. (String) | | Race | The race of the director. (String) | | Director(s) | The name of the director(s). (String) | | Film | The title of the film that won the award. (String) | | Nomination/Winner | Whether the director was nominated or won the award. (String) |

Acknowledgements

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

Intoduction The Academy Awards, popularly known as the Oscars, are awards for artistic and technical merit in the film industry. Given annually by the Academy of Motion Picture Arts and Sciences (AMPAS), the awards are an international recognition of excellence in cinematic achievements as assessed by the Academy's voting membership. I wanted to visualize the diversity in academy awards (Oscar awards), but I was unable to find a complete dataset of all nominations and winners for all categories with their respective gender and ethnicity from 1927 to 2020. I found a basic dataset from Kaggle, but it did not have gender and race of the nominations and winners.

Content Description Coloumn 1: year_film; the year in which film was realesed.

Coloumn 2: year_ceremony; the year in which the movie was nominated Coloumn 3: ceremony; Oscar ceremony number Coloumn 4: Category; Oscar category for which it was nominated Coloumn 5: Gender; gender of nominee or the winner Coloumn 6: name; name of the nominee or winner Coloumn 7: Race; racial profile (ethnicity) of the nominee or winner Coloumn 8: film; name of the nominated film Coloumn 9: winner; True for winners, False for nominations only

Acknowledgements We wouldn't be here without the help of Raphael Fontes, who is the source for the basic dataset.

Inspiration 1. Do the Academy Awards reflect the racial diversity of films or are the #OscarsSoWhite? 2. Why did the academy introduce new set of rules for diversity? Why was it required? 3. Is there an equal representation of men and women in the entertainment industry?

For years, the number of Academy Award nominations for Netflix increased, peaking in 2021 at ** nominations. Since then, the Oscar nomination count for the streaming giant declined and amounted to ** in 2025.

In 2025, around **** million Americans watched the Academy Awards ceremony. Oscars viewership fluctuates year by year, however, the last time the ceremony drew in a U.S. audience of more than ** million was back in 2014. The figure recorded in 2021 was the lowest yet, and marked a drop-off of over ** percent from the 2020 audience. Coverage of the Academy Awards Viewership of awards ceremonies can depend on multiple factors, ranging from personal preferences to overall interest in nominees, as well as how much coverage is devoted to the ceremony before and during its broadcast. Interest in upcoming events in the media industry is often generated via social media, which can be extremely effective in generating discussions, interactions, and general awareness. In 2018, the Academy Awards were mentioned *** million times on social media during the ceremony, and have also proved to be some of the most popular TV specials on Twitter in recent years. Conversely, a survey held in early 2019 revealed that ** percent of U.S. adults had not come across any news coverage for the 2019 Academy Awards at all.

About a quarter of American moviegoers agreed that the Academy Awards had a diversity problem and that the nominees were not diverse enough in terms of race, gender and nationality in 2025. On the contrary, less than 35 percent disagreed and thought that the Oscars were diverse enough.

In 2025, Netflix received the highest number of Academy Awards nominations, with a total of 16. It was closely followed by independent studio A24 at 14 nominations.

Community OSCAR

The OSCAR project (Open Super-large Crawled Aggregated coRpus) is an Open Source project aiming to provide web-based multilingual resources and datasets for Machine Learning (ML) and Artificial Intelligence (AI) applications. The project focuses specifically in providing large quantities of unannotated raw data that is commonly used in the pre-training of large deep learning models. The OSCAR project has developed high-performance data pipelines specifically… See the full description on the dataset page: https://huggingface.co/datasets/oscar-corpus/community-oscar.

This is a dataset containing data on all the winners of acting Oscars from 1928 to present. Data includes names, films, ages and nationalities.

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In 2025, women accounted for 27 percent of the nominees for the main non-acting categories at the Academy Awards, down from 32 percent a year earlier. Only 20 percent of the nominees in the Directing (Best Director) category were women in 2025.

Comprehensive dataset containing 18 verified Oscar locations in United States with complete contact information, ratings, reviews, and location data.

Financial overview and grant giving statistics of Oscars Animal Sanctuary & Injury Shelter

This spreadsheet gives the most recent actual and forecast income and expenditure for the current financial year that The National Archives has submitted to Treasury. OSCAR is used by the Treasury to collect financial data from across the public sector. The data is used for fiscal management, producing Parliamentary Supply Estimates and public expenditure statistics, preparing Whole of Government Accounts and meeting data requirements of the Office for National Statistics.

This dataset represents the results of the experiment Progression of Revenue and IMDb Score of Oscar "Best Picture" Winners From 1986 Until 2016. Its latest released version of source code can be found at https://doi.org/10.5281/zenodo.4661145.

In 2025, "I'm Still Here" won the International Feature Film category at the Academy Awards, marking Brazil's first victory. Italy and France, however, top the ranking of this category with 11 and nine wins, respectively. Spain and Denmark tie in third place, each with four Oscars for International Feature Film.