This Chapter focuses on the development and application of keywords and rule-based systems for emotion detection. These systems, built on predefined rules and patterns derived from specialised lexicons and expertly annotated datasets, provide a structured and interpretable approach to identifying emotions in texts. By utilising lexicons and annotated datasets, researchers created models that could detect sentiment and emotional nuances with a practical degree of accuracy. In the following, we detail the context, methodologies, and key developments in keywords and rule-based emotion detection, highlighting the foundational role these systems played in the evolution of more advanced emotion detection techniques. We finally discuss the advantages and limitations of the key-word and rule-based approaches, highlighting their continued relevance in current emotion detection tasks.