While its publishing company had produced comics since 1939, Marvel Comics was truly established in 1961 with the creation of the Fantastic Four. Marvel followed up with Spiderman, the Avengers and the X-men, superheroes that would become the foundation of the now 7000+ stable of characters.
At the time, Marvel set itself apart with the creation of the “Marvel Universe”, a shared setting in which its characters existed and interacted. A sales gimmick developed from cameos and brief crossovers into a complicated web of stories featuring dozens of characters told across numerous titles.
This network visualization presents the connections between characters over decades of history, highlighting the ones who have made an impact on the Marvel Universe.
- The Marvel Social Network Gephi file – This network of superheroes was constructed by Cesc Rosselló, Ricardo Alberich, and Joe Miro from the University of the Balearic Islands. The data was collected by Infochimps and transformed and enhanced by Kai Chang.
- Gephi – It is an open-source software for network visualization and analysis. It helps data analysts to intuitively reveal patterns and trends, highlight outliers and tells stories with their data. It uses a 3D render engine to display large graphs in real-time and to speed up the exploration.
Because it was such a large dataset my first step was to use the Degree Range filter to exclude any nodes with a degree less than 750. I felt that using the entire dataset clouded the findings and was visually unappealing. Setting the filter between 1 and 750 added nodes but did not look better or reveal anything in the data that 750 didn’t clearly illustrate.
I tried most of the layouts but ultimately settled on ForceAtlas2. It allowed me to centralize the larger nodes while clustering the closely knit groups together. I calculated the Modularity to identify 4 groups, Fantastic Four, Avengers, Spiderman and X-men, and colored them accordingly. The X-men are green, the Fantastic Four is orange, Spiderman is blue and the Avengers are pink.
Wolverine, Iron Man, Spiderman and Captain America are the most featured characters. Spiderman is less central due to less connections with the Avengers group of characters. Despite not having the sustained popularity of Spiderman, Wolverine etc. the Fantastic Four were the preeminent Marvel characters for decades and remain large and central nodes in the Marvel network.
The X-men are pretty insular, while X-characters who have made a significant amount cameos like Wolverine and Professor X and who have been on other teams like Beast and Iceman larger and drawn toward the center.
Gephi is a program that can do interesting things but I found it awful to use. It’s really complicated, has no way to undo actions and requires constant saving. After watching several tutorials, playing with the program and doing this lab, I feel like I only have a basic understanding of the program and it would take working with several different types of datasets to be able to completely learn it.
I probably should have used a different dataset to learn the program with. While the size helped to illustrate how differently Gephi can visualize the same data, it was hard to make an appealing, informative, visualization with that large a network