In this episode, we’re joined by Dr. Valerie Hasse from LMU Munich to demystify one of the most widely used tools in computational text analysis: the dictionary. Valerie explains how computational dictionaries relate (or don’t!) to the everyday dictionaries we know, and breaks down how they actually work behind the scenes. We explore what dictionaries are good for, when to build your own versus using ready-made ones, and where they shine — especially for studying opinions, emotions, and media narratives. Valerie also opens up about the real challenges that come with using dictionaries, from biases to technical hurdles, and whether they still matter in the age of large language models. She gives clear answers and practical insights into a tool that helps researchers decode massive amounts of text.