On Stage Design Indaba 2019: Ellie Frymire

Ellie Frymire wanted to know what people were really saying with the social movement, #MeToo. With a background in coding, analytics and design, she looked at what themes and topics were most prominent in the conversation using unsupervised machine learning algorithms, which allowed her to make inferences from data sets.

Called k-means clustering, this made it easy for her to understand the movement’s growth and underlying issues. Frymire illustrated her findings on an interactive webpage. By hovering over the groups she identified, users can read the stories and learn more about the various clusters.

She identified these clusters by scraping through 1,4 million tweets and discovering 5 major themes: politics, workplace, anger, conversation and uplifting. For instance, she discovered that the word ‘power’ came up often in tweets about sexual assault in the workplace.