The Dark Knight | Data Science Approach on one of the Greatest Movies Ever Made
The Dark Night. . . The comic book movie that is considered, by many, as more than just a comic book movie. It was powerful enough to draw audiences outside of the comic fanbase, and even the Batman fanbase. Since its release in 2008, Christopher Nolan’s The Dark Knight has not only been commercially successful but is also considered by many as one of the greatest movies ever made, the greatest superhero movie, and one of the finest movies of 21st century.
Director Christopher Nolan has been known for his dark tone and realism in his movies. But he is also known to combine multiple genres all together to tell an epic story. Based on the iconic comic book characters Batman, the Joker, and Two-face, the second grand entry of The Dark Knight Trilogy combines superhero fiction with neo-noir, disaster fiction, and grounded action sequences. The film trilogy also drew inspiration from the graphic novel “The Killing Joke” and the 1996 series “The Long Halloween”.
Many professional critics wrote their pieces on The Dark Knight and 2,216,966 IMDb users rated the movie on IMDb, making The Dark Knight the second most voted movie in IMDb after Shawshank Redemption. Now, it’s time to use the data science approach to learn from critics and IMDb users.
Rotten Tomatoes is one of the most popular review-aggregation websites for film and television. For each movie, Rotten Tomatoes has a Tomatometer (avg. scores of critics) and an Audience score. It’s all public and extremely easy to retrieve. But Rotten Tomatoes also contains headline reviews from critics with external links leading to the full review. Headline reviews are a paragraph of comments by the critic giving their overall thoughts about the movie.
The Dark Knight (2008)
Christopher Nolan steps back into the director’s chair for this sequel to Batman Begins, which finds the titular…
The Dark Knight received 338 critical reviews, including reviews by the top 63 critics. Top critics are highly respected and their words are highly valued by readers and media. For this project, the headline reviews from the top 63 critics were retrieved, cleaned, and analyzed. The figure below shows the word cloud of the headline reviews.
We can observe words like “entertain”, “best”, “like” and other praiseful words. We can also see that Heath Ledger and Christopher Nolan’s names are mentioned.
Similar to Rotten Tomatoes, Metacritic is a website that aggregates reviews of films, TV shows, music albums, video games and formerly, books. For each product, the scores from each review are averaged. It also contains headline reviews from well-known movie critics. Metacritic is known for being more critical than Rotten Tomatoes with their scores.
The Dark Knight
Summary: Batman raises the stakes in his war on crime. With the help of Lieutenant Jim Gordon and District Attorney…
The figure below shows the word cloud of the headline reviews.
We can also observe critics mostly discussing Heath Ledger’s Joker, Christopher Nolan’s work, and Christian Bale’s Batman.
Critics are highly praising the movie, especially towards Nolan’s direction, Ledger’s performance, and the action sequences.
IMDb is an online database that contains information on movies, television series, home videos, video games, and streaming content online. It also includes cast, production crew, personal biographies, plot summaries, trivia, ratings, and reviews from critics and fans.
Demographic (age group & sex) of voters in IMDb for a specific show or movie is always public.
Twitter is a highly used social media platform. Folks tweet almost about everything. Now is time to look at what public data can tell us. We can get public tweets from Twitter, clean it up, store it into a data frame, and visualize it.
For this study, 20,000 public tweets written in English with #theDarkKnight were analyzed.
Character Network Analysis
Can our approach go further? The answer is yes. We can certainly do something really interesting by visualizing the relationships between the main characters of the movie.
Network Analysis is a set of methods used to visualize networks and describe specific characteristics of overall network structure. Here, we will analyze the network of characters in The Dark Knight. Rather than just showing one simple random network, we can experiment with different kinds of layouts without a network.
We can specify the layout for the plot. That is the (x,y) coordinates where each node will be placed. R package
igraph has a few different layouts built-in, that will use different algorithms to find an
optimal distribution of nodes.
Bruce Wayne/Batman is the protagonist. He has allies to fight alongside with, villains to face off against, and a love interest who also caught the heart of a villain.
The most popular layouts are force-directed. These algorithms, such as Fruchterman-Reingold, try to position the nodes so that the edges have a similar length, and there are a few crossing edges as possible. Our goal is to generate layouts, where nodes that are closer to each other share more common connections than those that are located further apart.
Notes: Choosing a different seed will generate different layouts.
The Dark Knight has revolutionized comic book movies with its gritty and dark tone, inspiring many movies of the future. The movie has been used as a commentary on fighting terrorism, pushing the boundaries of civil rights, and mental health. The movie intentionally does not show the origins of the Joker, keeping it a secret to have the fans constantly buzzing until a later time where there might be a standalone feature on the Joker. There have been many theories saying that Joker is a war veteran who suffered from PTSD before his mental breakdown. The movie is an enjoyable art for discussion and this art is the reflection on the society of the 2000s.