How right is Nolan in his perspective on the length of films?
Christopher Nolan defended the extended duration of his recent film ‘Oppenheimer,’ addressing concerns about its length. He emphasized that historically, successful films often have longer runtimes. According to Nolan, the key is audience engagement — if viewers are captivated, a three-hour movie is acceptable. Reflecting on my favorite films like ‘The Lord of the Rings,’ ‘The Matrix,’ and ‘Braveheart,’ I realize they too exceed typical durations. Curious about the broader trend, I plan to use Power BI to visually explore the correlation between movie success and runtime.
IMDB (Internet Movie Database) data set is one of the most comprehensive data sources about the movie industry. This dataset contains many movie-related data such as movie summaries, actors, directors, movie duration, box office revenues, etc. Hence, I opted to analyze The Top IMDB 1000 list on Kaggle.
The csv file we downloaded from Kaggle looks like below.
We will focus on specific columns — runtime, rating, metascore, and gross. Additionally, I’ve introduced a new runtime classification in Power Query, marking films exceeding 150 minutes as ‘L’ (Long) and those under 150 minutes and above 40 as ‘M’ (Moderate).(none below 40)
Adding a new column to data; Table.AddColumn(each if [Watch Time] >= 150 then “L” else if [Watch Time] < 150 and [Watch Time] > 40 then “M” else “S”)
This is how the table appeared after the inclusion of the new column.
Now, let’s move on to visualization.
Dataset Insights: Unveiling Key Statistics
Runtime: The duration or length of a movie, measured in minutes.
Rating: IMDb ratings are based on user reviews and ratings. Users can rate movies on a scale of 1 to 10, and the overall rating is the average of these user ratings.
Metascore: Developed by Metacritic, compiles reviews from critics and publications, assigning a weighted average score on a scale of 0 to 100. A higher Metascore signifies favorable reviews from critics.
Gross: typically refers to the total box office revenue generated by a movie. This figure represents the total earnings from ticket sales during the movie’s theatrical run.
The key observation here is the notable disproportion, where the quantity of long films is roughly five times smaller compared to moderate ones.
Exploring the Relationship Between Rating and Runtime
As evident in the graphs, there appears to be a slight increase in average ratings (7.8–8.2) as movie duration extends in the scatter plot. This suggests a correlation between film duration and audience appreciation.
Exploring the Relationship Between Metascore and Runtime
As observed in the graph, the fluctuation in Metascore remains within acceptable limits, indicating no significant discernible difference.
Exploring the Relationship Between Gross and Runtime
Above, the discernible correlation between duration and gross becomes evident, mirroring the observed connection between duration and rating. Furthermore, upon comparing by year, it becomes apparent that films released after 1990 exhibit higher grosses.
5. Conclusion
In light of the comprehensive analysis encompassing various data and visual representations, a positive correlation emerges between the length of films and their reception, both in terms of audience appreciation and box office success. Consequently, it can be affirmed that Nolan’s perspective on this matter appears to be substantiated.
