Culture is not the most common topic in data journalism. We wanted to see how the role and share of women in Finnish film industry has changed during the years. Hypothesis was that 2010´s was the decade when women truly had a big role in making movies.
We didn’t look at actors but concentrated on directors, producers, writers, camera(wo)men etc. The data was from years 1913-2020.
The main impact was that the story showed how in Finland women have never made as many movies as today.
Our data also had ratings of the movies so we could show that nowadays movies directed by women get more viewers on average than those directed by men. This is a historical change.
The movie data for the story was collected programmatically by Python from the Finna open API. Finna is search service that collects cultural and scientific material from hundreds of Finnish organizations under one roof.
The data consisted of almost 5000 movies ever made in Finland together with various metadata, most importantly the names of authors, actors and makers and their roles in the movies and the year of publish.
We had previously made a simple Node.js function to label names by gender, so we used that to see how the makers of Finnish movies are separated into women and men. From this data we then got multiple gender distribution timeseries, for example how many
female directors/writers/actors/etc. there has been yearly in the past 70 years in Finland.
We used Python, Node.js and Excel in the analysis. At the end of the story there is a small search engine where the user could filter all the female directed Finnish movies by decade, genre and free search. The search engine was done with Vue.js.
What was the hardest part of this project?
The hardest part is to get culture journalists (how know their field well) and data journalists to get together and create new data driven ideas that benefit traditional culture journalism.
What can others learn from this project?
That data journalism can and should be done about culture as well. News are there to find.