Uncanny X-Men
Physical Contact Between Characters
Issues 250 -290
Thicker lines indicate multiple instances of physical interactions between characters.
The Why?
One of my hobbies is illustrating character designs for stories, and so I was drawn to the datasets covering the Uncanny X-men comics. After considering the datasets we had in the midterm folder, I decided that my midterm would be taking the form of a network analysis by cleaning up data of physical contact between characters in the Uncanny X-Men comics provided by the Claremont Run‘s data sheets. For context, the Claremont Run is a project exploring comic book writer Chris Claremont‘s sixteen year run on Uncanny X-Men from 1975-1991, and the impact on gender and sexuality in comics, which has dominoed into long continuity in modern media. Chris Claremont is one of very few writers who stays on a series for more than a couple of years, and he is accredited for developing complex literary themes into the superhero narrative as well as strong fremale characters. I hope creating a visualization of information captured in the datasets I can help visualize the social dynamics.
The What
With this information, the dataset that I used for this project, Uncanny X-Men Character dataset, had contained information about the characters’ appearances, affiliations, powers, relationships, and physical contact in each comic issue. Our midterm data pool had data was reserved to issues 250 to 290. I was particularly inquisitive in the columns related to physical contact, which records the instances of characters coming into physical contact with each other, such as hugging, kissing, holding, or flying next to. I wanted to explore how this column could reveal the patterns of interaction and intimacy among the characters.
The Presentation
To visualize the network of physical contact between characters, I used Flourish’s network graph template. I uploaded my CSV file and adjusted the settings to use the default graph that showed the nodes (characters) and edges (physical contact). I chose Flourish because it was easy to use and embed on my WordPress website, where I created a landing page and our class blog posts before. I also added some annotations and captions to explain the graph and highlight exciting findings.
The Process
I used OpenRefine for data cleaning and formatting to prepare the data for network analysis. The main steps I took were removing all the columns without data or only included true or false binaries, such as if they were incapacitated, declared dead, had clothing torn, etc. These columns were irrelevant to my research question, which focused on character interactions. I then made facets of all the character interaction columns and filtered for blanks for characters who did not interact with anyone. Because the midterm data set was an excerpt of a larger data pool, there were a lot of values that did not have an associating attachment because they were based on characters’ appearance in comic issues. I sorted the data alphabetically by the characters’ names to make finding and editing them more straightforward. I made sure that names were clustered to both include the hero and civilian names so it would be read as the same character in the network chart. I created a new “value” column based on the physical contact column because it had the most characters. I assigned a numerical value to each type of physical contact, ranging from 5 (low intimacy) to 20 (high intimacy). For example, a hug would have a value of 10, while a kiss would have a value of 20. I did this to quantify the strength of the relationship between the two characters. Every instance of each contact added into a sum of amount of interaction between two charcaters. I exported the data as a CSV file with only three columns: character 1, character 2, and value.
The Significance
By applying network analysis to the Uncanny X-Men Character dataset, I gained some insights into the characters’ social dynamics and emotional bonds. For example, I found that:
- The most connected character in terms of different charcaters in contact with was Wolverine / Logan, who had 16 edges with different characters. This suggests that Wolverine was a central and influential figure in the X-Men team who had various relationships with other characters, such as friendship, romance, rivalry, or mentorship.
- The highest value of physical contact was between Jubilee and Wolverine, who had a value of 110. This indicates that they had a solid relationship, which is surprisingly unromantic. Jubilee is Wolverine’s unofficial sidekick in the X-Men team, whereas the second highest interaction count was between Banshee and Moira MacTaggert, which is romantic.
- The network graph also showed some clusters and subgroups of characters who had made contact with lots of characters. For example, a cluster of female characters, such as Rogue, Psylocke, and Jubilee. There was also a subgroup of villains who frequently fought with each other or with the X-Men, such as Professor X, Magneto, Mystique, and Pyro.
My project relates to Digital Arts and humanities instead of data science because it uses digital tools and methods to explore a creative and cultural artifact: the Uncanny X-Men comics. By applying network analysis to the character interactions, it supports some aspects of the narrative and aesthetic choices made by the authors and artists of the comics, as well as some themes and issues that resonate with the readers and fans of the genre.