Blog Post #7

Unfortunately, I didn’t get my Tableau data visualization to work in the lab, however, Robots Reading Vogue was extremely interesting for me, and one of my favorite projects in DHSS to explore.

The tool I played with most in Robots Reading Vogue was the n-gram. This tool keeps track of the amount of times any word(s) the user types in has been used across all issues through all of time. As you can see here, I typed in the words “woman”, “girls”, “makeup”, and “dress” and what I’ve discovered is extremely interesting (well, interesting to me at least). I found that the term ‘makeup’ wasn’t a real trend until the early 60’s, and this can probably lead to the conclusion that for the most part, women had a completely natural look for the most part. The 60’s was an era where fashion took a complete 360 turn and could be a factor as to why makeup trended tremendously.

Another interesting phenomenon I see is that every time the term “women” is used more, “girls” is used less, and vice versa. It’s essentially like an inverse phenomenon, which I find pretty amazing. Towards the 2010s, they seem to be leveling out, but ‘girls’ is used less, and ‘women’ is more prominent, most likely because of empowerment and feminism. In the 20’s and late 40’s-50’s, ‘girls’ is used more, and an assumption can be made that it may have been used more as those times are when men were coming home from war, and women girls could have been seen more as a product and advertised more when the men were coming home from war.

Try the N-gram out for yourself and have fun with it with your friends, and try to come up with some interesting/hilarious terms and look at some trends!