Machine Learning in the Wild: Techniques for Understanding your Audience

GOTO Berlin 2017

A common problem facing media companies is the task of understanding who their audience is and what content holds their interest. This can be especially difficult when most users interacting with that content are anonymous. However, a number of machine learning methods can be applied to audience data to gather insights and help content creators make better data-driven decisions.

In my talk, I’ll walk through several examples of my work at Mashable where I’ve applied machine learning to helping us understand different aspects of our audience, such as who they are, what content is important to them, and the social media strategy used to deliver that content. I’ll go in depth with the algorithms I’ve used and the data that I’ve worked with to deliver useful insights to our editorial team. I will demonstrate that, even though audience data can be tricky to work with, it can be very advantageous to do so.

Prerequisite attendee experience level: Advanced