About This Talk
The Harry Potter series is an incredibly popular franchise that shaped a generation, but it’s also been critiqued in the media and academics for its sometimes sexist portrayal of female characters. This talk uses Natural Language Processing techniques and Python to do the first quantitative analysis of gender bias in the language used to describe women and girls in the series, with a focus on Hermione Granger, the unsung hero of the story. Attendees will see techniques for reading and parsing large text files, leveraging grammatical rules to isolate the right words for the analysis, and data visualization techniques, using Python, the Natural Language Processing Toolkit (NLTK), and Matplotlib. After the talk, the audience will be able to get started on using the “magic” of programming to isolate biased language in any piece of text.
Eleanor Stribling is a product manager and developer with a passion for using software to help solve difficult human problems. Her interests are around using software and data to help us make better decisions and developing interfaces that make human and computer interaction more intuitive, accessible and conversational. In her ten years in the tech industry, she’s had leadership roles in in both tiny startups and large multinational companies, building software rooted in data applications for the ad tech, energy, and HR analytics. A lifelong learner currently leveraging her background in Python and analytics to become an expert in AI and Natural Language Processing, she is an alumna University of Toronto and the Massachusetts Institute of Technology. Eleanor lives in San Francisco with her amazing family.