So this is the first part of my dataset project. During Halloween, after a couple hours of binge eating fun-sized candy bars and marathoning various scary movies, I got the idea to use horror films as a dataset for this class, given my personal and semi-scholarly interests in the genre. Obviously, this deviates from my research on early modern literature, but I am not new to using horror films as the focus of other academic research.
With that half-baked idea in mind, I set out to narrow my focus a little to get a central theme for the data that wasn’t just the genre itself. I decided to exclusively use films made in the 1980s, a decade for horror films that was especially prolific. Many of these horror films, such as They Live and The Stuff, served as thinly veiled political commentary against an increase in enthusiastic republican politics and capitalism. Wes Craven, popular horror director, explained in the horror movie documentary Nightmares in Red, White, and Blue that he “wanted to do something about Reganism…The crowd was ‘kill a commie for Christ and let’s get those commies and kill them’ something I grew up laughing at in Dr. Strange Love. Now here it was again. It returned and with this massive enthusiasm behind it.” Even as some horror movies served as seemingly progressive political narratives, the genre was also at the peak of slasher films in this decade, a subgenre that has been especially criticized for its violent misogyny, a theme that Wes Craven also participated in with movies like Last House on the Left and A Nightmare on Elm Street.
After narrowing my focus, I started collecting my dataset, using Wikipedia’s horror movie list (separated by decade) and IMBD respectively. I ended up with 610 movie entries, a small dataset but totally usable in my opinion. I catalogued the title, date, director, and country of origin for each film, hoping to utilize this information.
Now, before I continue with this project I face a couple of predicaments with where I want to take this project. I would really love to catalogue the instances of violent misogyny, as subjective as that may be, and perhaps utilize a digital tool/platform that would showcase repeat offenders by year, director, and country of origin. The problem is, there are over 600 movie entries, not all of which I’ve seen or remember intricate details of, so cataloguing those instances or themes of violent misogyny would be difficult, subjectivity aside. I suppose I could rely on synopses and critic reviews, but I’m not sure if that would provide the best results.
The other problem I’m running into is finding a graphing tool that will be able to showcase the dataset for the particular variables I’m interested in (i.e. cataloguing themes of violent misogyny by date, director, and country.) I am leaning towards Gephi since I’ve been playing around with it lately, but I’m definitely open to any other suggestions, as well.
I think this would be interesting to look at quantitatively. I don’t know if you could get this kind of information from IMDB, Wikipedia or other fan sites, but I’m thinking about numbers of people killed. So, who is the first person killed in each movie and their gender? Possibly also the number of minutes into the movie they are killed. And then total number of people killed, with subtotals for number of women and number of men. You could then use R to find some basic stats about these things, and graph them. Are there trends in how quickly someone is killed, and does their gender affect this? Trends in sheer number of victims? Of women? Of men? Are there movies that are considered horror films where no one dies? What, if anything, does this say about our collective (or the horror movie watching population’s) interest in mass violence? I’m assuming most directors are men, so does the gender (or nationality) of the director have an impact on these things–maybe I am getting into the correlation does not equal causation territory here.
If you wanted to make your dataset smaller, you could randomly choose 10 movies from each year. That would give you a significantly smaller size to collect data on, but would still give you a statistically significant amount of data to work with–I think. Proper statisticians could weigh in on this. Or you could limit by country (and also by random sample per year) if you wanted to narrow the potentially confounding factors.
Sounds weird and fun. Sounds like Sarah has a good idea for making your data set more manageable.
Can’t wait to see.
Horror is a great genre for measuring social anxieties. Quantifying sexism is tricky though. Violence against women is omnipresent in these films, so one variable you could look for is the perpetrator. One method could be categorizing the killers or threats in these films into certain types, such as super natural beings, aliens, scientists run amok, serial killers, etc. Then you could break down from the killer to the film’s country of origin. Or you could go with the number of women killed by entities that identify as male, female, non-binary or other (check out Sleepaway Camp to dwell on that one).
Of course there are films that genre bend things in ways that might make quantifying them difficult. Take Cronenberg’s Videodrome for example; women are killed and brutalized in it, but the perpetrators range from unknown hooded figures, to a subliminal signal sent through television. John Carpenter’s The Thing didn’t even have any women in it (unless you count the computer chess game which used a woman’s voice). Aliens hopscotches between war film, sci-fi, horror, and some kinda metaphor where Sigourney is an “earth-mother” fighting off an alien and nuclear threat.
It also might interesting to see what films were banned or censored in what countries. Britain’s video-nasties campaign of the 80’s to purge violent video tapes which only made them more desirable could be contrasted/compared with data from the explosion of video rental stores across the globe and how horror was flocking to this new medium. Kinda like the propagation of speakeasies during prohibition.
This is so cool!!! I think this data analysis needs to happen. There is so much violence against women in horror films. I am glad to see someone else breaking away from their period of focus into more contemporary stuff. It gives me hope for what I am doing. Speaking of which, I saw your post on Great Expectations. I didn’t know you were interested in the 19th century, so we should definitely chat! I also think it would be cool to do data vis with Dickens at some point–particularly with his networks of female collaborators.
One possible way to capture qualitative data about violent misogyny, might be via film reviews. I know that there are archives a film reviews available (I even stumbled across one in the early days of working on my data project. I just can’t remember exactly where it was. I think it was one of the resources cited in Digging into Data). You could search the reviews for the titles of the films in your list and look for matches on keywords that would suggest violence against women. That is a lot of work, but it would be less work than hand cataloging the metadata for each film in your database.
I know we spoke after class and during class about this project, but just to post here too–I think this is a really inspired piece of work, and like Kelly has done, I love that you’re thinking about how data visualization can affect the way we perceive our own experiences.
A crowdsourced submission platform like Tumblr could be an interesting way to collect results, and could also potentially remove the subjectivity issue by embracing subjectivity as part of this. Instead of the singular author of the project acting as determiner of sexual violence towards women, it could be determined communally.
That being said, I do not underestimate the risk of taking a feminist stance on an issue of sexual violence, particularly when data may be derived from topics that have rabid and protective male fan groups, but that will be an issue that you can negotiate in your choice of platform/publication, as well as where you choose to go with the effect you’d like this project to have outside this course.
Best of luck! Let me know if I can help in any way!