This article presents a new model for emotion mining, resulting from the research project Embodied Emotions. This project aims: 1. to trace historical changes in emotion expression and in the embodiment of emotions, and 2. to develop methods to trace these changes in sizeable corpuses of digitized texts. Up to now, the mining of sentiments or emotions has mainly been restricted to modern, or even very recent text corpora, such as social media. Sentiment mining techniques are often based on relatively simple emotion models of binary (positive/negative) oppositions, or limited sets of ‘basic’ emotions and are not yet able to deal adequately with the complexity and the historical contingency of emotions and their expression. To meet these challenges, we have developed the Historic Embodied Emotion Model (HEEM), built on a test case of 29 Dutch language theatre plays written between 1600 and 1800 and annotated manually with HEEM labels for emotions and body terms. In this article, we present this model and compare it with other sentiment mining techniques: 1) off the shelf linguistic analysis software LIWC (Linguistic Inquiry and Word Count), 2) a version of LIWC that has been adapted for the analysis of Dutch historical texts, 3) a new Dutch translation of WordNetAffect. We conclude that, although different forms of sentiment mining have their value and use, HEEM provides new opportunities for emotion mining and analysis of embodied emotions in historical texts.