In this episode, we’re joined by Prof. Damian Trilling from Vrije Universiteit Amsterdam, who opens the door to the world of machine learning for opinion research. Damian explains how citizens consume and share news today — and how machine learning helps us make sense of these patterns at scale. We unpack the difference between supervised and unsupervised machine learning and explore how blending both can strengthen research projects. Damian also shares why these methods hold so much promise for the future of studying opinionated communication and news use in the digital age.