## 5 User Understanding
### Emotion Analysis  
As has been highlighted by [80], cultural heritage sites are places where visitors go not only to enrich their knowledge, but also to experience emotions. The research reported in [80] has shown that focusing the visiting to only recreational or learning goals is too simplistic: museums and heritage sites are exploited and visited in many various manners and with different objectives, depending on the specific purposes of each visitor. Furthermore, interpreting and understanding how people make use, interact and catch the essential elements of a cultural heritage site makes is important. According to this premise, an automatic system for emotion detection and recognition involved in Human Computer Interaction (HCI) and Affective Computing (AC) can play a crucial role [81]. These systems can catch the visitors' emotions and, subsequently, the information can be exploited to improve the visiting experience of the users. Emotions characterize one of the most fundamental ingredients of human behavior. This aspect can be effectively exploited in human-computer interaction by using an artificial intelligent system at the basis of an advanced cultural heritage system, constituting an essential feature of one of our four pillars approach. The system could recognize the emotions of the users and exhibit an empathetic response emulating a truly intelligent behavior. Human beings manifest their emotions in many forms, including both explicit, indirect and non-verbal means--facial expression, speech, using specific utterances; sometimes, the use of irony or sarcasm can make it very difficult to recognize the exact expressed emotion. According to a study illustrated in [82] four aspects are tackled in recognizing emotions--facial expression recognition, physiological signals recognition, speech signals variation, and text semantics. To highlight the prominent role played by emotions in cultural heritage, a methodology aimed at researching the relationship between cultural heritage spaces, emotions, and visitors has been presented in [83]. A case study, based on \"Tredegar House\" in the United Kingdom, has been illustrated. It aims to determine whether the Tredegar House can be a site capable of eliciting affective experiences and, if so, of what kind. To answer this question, visitor physiological data is captured, a post-visit survey is conducted, and some ethnographic notes are also considered. Each participant at the site entrance wears a device that measures different parameters, such as blood volume, pulse, heart rate, electrodermal, temperature, and accelerometer. Cardiac and electrodermal activities were considered in the study. After crossing two gardens, visitors decide whether to continue the view as \"lady\" or \"maid,\" following two different routes. At the end of the visit, participants filled out a questionnaire asking what visitors found interesting during their visit, the emotions they felt, both with open-ended and closed-ended questions, and were asked to describe how these emotions had been triggered. The goal of the study was to identify if there are any relationships between how an experience is subjectively reported and physiological response, highlighting the value of qualitative data combined with digital tools. A mobile application that supports the visit of cultural sites associated with the person of the musician [PERSON] has been presented in [84]. The system exposes a human-machine interaction mode based on the user's mood while exploring various sites of interest. The content that is shown to the user is driven by the state, the mood, of the person using the proposed system. In particular, the app, called \"VersoVerdi\", visually identifies the user's mood, which can be \"happy\" or \"unhappy\". Based on this information, the system provides suggestions of content to display corresponding to the mood identified. The system can also suggest links between museums: each museum is metaphorically shown as a planet.