Critical Creation
Male Data Set: https://w.wiki/7s6f or https://w.wiki/7s6h
Female Data Set: https://w.wiki/7s6n or https://w.wiki/7ppk
I decided to filter out superheroes within comics on the basis of gender. Starting my search I expected the underrepresentation of women as superheroes in comics. Most superheroes that we see are male characters. In this process, I made two graphs, one with male superheroes and the other with female superheroes. This search wasn’t limited to a specific company such as Marvel or DC, it included a wide range of companies including Powder Puff Girls, Power Rangers, Storm Universe, etc. While adding my filters in my search I found eighty-five different female superhero characters from about forty different companies including the major ones such as Marvel Universe and DC. I then chose to put the information gathered into a scatter chart because it was easier to read and see how many characters belong to the same companies, and I was able to see which companies in this dataset had the most representation of females and which had the least.
Marvel Comics had the most representation of women superheroes with a total of twenty-seven superheroes. This information is interesting because when we think of Marvel heroes four only come to mind: Black Widow, Scarlet Witch, Captain Marvel, and Wonder Woman. Within our movies, we see the underrepresentation of women superheroes but from this finding, we see a representation of women superheroes within comics. I think this data suggests that whoever created this data set had a goal to represent women in their works because when we look at the data for male superheroes the results are surprising. The data set only pulls up twenty male superheroes versus the eighty-five female superhero characters. It’s interesting because I expected the number to be flipped. This data set only represents sixteen different companies in comparison to forty companies in the female data set. The creator of this data set goal had to be the representation of female characters in comics. He or she did a great job as I was introduced to new superheroes in the female data set and gained knowledge on new companies that produce these superheroes.
In the male data set, I don’t recognize any superheroes, which shows the creator went away from the popular and well-known male superheroes and brought in not-so-popular characters. Why? Is the creator trying to represent male superheroes that aren’t popular as well? I took a look back at my data set filters and saw that my filter was set to “fictional human” suggesting that other heroes may not be mentioned because they aren’t considered “human” in their universe. When I changed the search to the fictional character I was unable to even get a data set, which made this work hard. Taking a look at both data sets the roles were reversed, as the representation of women grew, the representation of men superheroes declined. My suggestion would be for the creator to create a data set where we are able to see every male superhero and another data set where we are able to see every female superhero. So we are able to see the actual misrepresentation of gender and fictional superhero characters. We would be able to compare the numbers and look at the different studios/companies and see which companies put in more female superhero characters, making the data so much more accurate. The inaccuracy is the only problem I see within the data sets, as I mentioned the representation is flipped by each gender which may have been a goal of the creator of the data set.