Data Explorations

Fall 2019
2–4 weeks
Exploring (and learning) ways to collect, parse, and visualize data.

Jump to: Tweet Trends | Women in Film 

Tweet Trends

How can twitter activity reflect a user’s interests and concerns? 

I aimed to represent the patterns of twitter activity over time, through the perspective of two different users. I focused on two students who lived through the shooting at Marjory Stoneman Douglas High School (MSD) in Parkland, Florida, and have embraced political and social activism through co-founding March for Our Lives (@AMarch4OurLives) with other student survivors. I compared their social media use and trends following political events in time. I used python and NLTK to scrape and parse tweents, and p5.js to generate graphics.
01. Tracking topics and volume over 21 months

Visualizing Women in Movies
with Audrey Zheng
The Bechdel Test, created by Alison Bechdel when it appeared in her comic Dykes to Watch Out For in 1985, examines the role of women in movies. It asks two questions:

1. Are there two, named female characters?
2. Do the named, female characters converse about something other than a man?

However, it remains a shallow examination of female characterization, and is limited as a tool for feminist critique. (It wasn’t designing as a method for analysis! But it says a lot when so many movies still fail to pass...) We wanted to examine how the most popular movies in our cultural psyche fared against not only the Bechdel Test, but other questions about the role a female character has and plays to the overall narrative.

Audrey and I manually entered in data for 200+ films, including cast ratio, bechdel responses, and other character informataion. She prototyped the interaction of the site, while I used the data to generate the main visualization with paper.js. Read about the full process here.
02. Prototype Home Screen03. Sorting every movie with Y/N questions, using paper.js
04. Male to female cast members, top 10 highest U.S. grossing films