Emotions of reading (JGU-QMUL), namely the emotions that the act of reading triggers and inspires in human beings, is one of the most hidden and complex aspects of our reading Cultural Heritage. This has hardly been studied because of the difficulty in detecting and characterizing emotions, especially in short texts and audiovisual content. In EUR-TRAIL, state-of-the-art and beyond state-of-the-art affective computing and sentiment analysis technology will provide the means to explore emotions of reading in textual as well as audiovisual sources at a scale never envisioned before. Emotional concepts will also natively be implemented in the EUR-TRAIL data model, producing a nuanced series of concepts about the emotions related to reading. Combined with advances in affective computing techniques for data linking, this will enable the development of new unchartered research directions in reading studies. Two tasks will be considered, focusing on distinct research questions. The first one focuses on digitized textual sources consisting of short testimonies in multiple European languages to discover what contemporary readers find pleasurable or displeasurable when reading certain texts, e.g., [reading is] “enriching, relaxing and a time for myself”, “a pleasurable hobby”. The actual study of these testimonies requires EUR-TRAIL to design text categorization and clustering techniques as well as interfaces to facilitate their enrichment and exploration. The second use case considers audiovisual sources in English produced by visually impaired readers, raising challenges in affective computing from nonverbal cues jointly obtained from audio and video sources, here again to gain insight into what makes reading pleasurable for this specific population. Making available sources relating to blind, partially sighted, and sighted readers in a single unique research environment will also foster comparative research questions bound to impact policy makers’ and NGOs’ work towards an inclusive society.