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Spanking and Spreadsheets: Data-driven Sex Journalism

Nolis, Jacqueline; Nolis, Heather

When we saw that the Stranger, Seattle’s alternative newspaper, was running a survey on kinks and sexual preferences, we knew we had to get our hands on the data. We convinced the that using machine learning methods on the responses would be a good idea, and then we quickly set out to analyzing them. But we had never written an article for a newspaper before—nor had we worked with data even remotely as dirty. It turns out what makes for a good blog post or technical journal is very different than writing for print, especially for such a sensitive topic. In this talk we will cover how we made sense of the lewd data, the statistical methods we used (and failures we produced), as well as the final results that ended up in our feature article: “There Are Four Kinds of Sex Partners (which one are you).”

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