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For our October event, R-Ladies Yipeng Lai and Stacy Lansey will share short talks on using R for analyzing gender bias on Wikipedia and learning R through data visualization (which motivated an interesting side project on gender).
This event will be hosted over Zoom, and the link will be available on this Meetup page at noon on the day of the event.
Agenda (times approximate):
7-7:05 pm: R-Ladies NYC Announcements
7:05-7:30: "Text Analysis in R: Gender Bias in Wikipedia Biographies" by Yipeng Lai
7:30-7:55: "R is for Resilience: Learning R through Data Visualization" by Stacy Lansey
7:55-8:15: Questions and wrap-up
--- Talk Abstracts ---
"Text Analysis in R: Gender Bias in Wikipedia Biographies"
Speaker: Yipeng Lai
Abstract: This talk will focus on how to manipulate and analyze textual data in R using the quanteda package. Yipeng will go over some basic natural language processing techniques. She will talk you through how to apply these techniques to dissect gender bias in Wikipedia biographies. She finds that biographies about female subjects are more likely to contain terms relating to gender and marriage.
Bio: Yipeng is an Applied Scientist at StreetEasy, NYC's local real estate marketplace. She just received her MS in Data Science from New York University this summer. She is passionate about natural language processing, data science for social good, and urban data. When she is not working with data, you can find her blogging about food and practicing latte art.
"R is for Resilience: Learning R through Data Visualization"
Speaker: Stacy Lansey
Abstract: I will talk about my first R Project, the visualizations for the Warby Parker Impact Report, and how I used the skills I gained to advocate for a shift in the descriptive adjectives associated with female students at my son's school.
Bio: Stacy Lansey is the Data Science Analyst at Warby Parker. She came to this role from a background in real estate and finance and is speaking about her experiences learning R in this role.
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