In this episode, Professor Mario Haim from LMU Munich breaks down what it really means for research to be robust — covering key concepts like generalizability, validity, reliability, reproducibility, and replicability. Mario explains how these ideas connect and why they matter, especially when studying opinionated communication with computational methods. He shares practical insights on common pitfalls, specific challenges in this field, and concrete steps researchers can take to strengthen their studies — from better documentation to transparent workflows and careful methodological choices. Whether you’re designing a new project or refining your research practices, this conversation offers valuable guidance for ensuring your work stands on solid ground.