Recently, the importance of designing tourism routes based on a comprehensive evaluation of tourist experiences has been increasingly recognized. One common approach for such an evaluation involves the use of electrodermal activity (EDA) data, a physiological indicator of emotional arousal. However, owing to the high cost and complexity associated with collecting and analyzing EDA data, their use in real-world tourism settings remains limited. Consequently, this study focused on the individual excitement level (IEL) curve as a subjective and cost-effective alternative for visualizing emotional transitions during sightseeing. Building on previous studies, we developed a web-based application that allows tourists to self-report their emotional responses with greater granularity. Unlike previous methods that use only three levels, the proposed system supports both a five-level positive scale (1 to 5) and an extended ten-level scale (−5 to +5) that incorporate negative emotions. We conducted a field experiment in Mojiko, Kitakyushu City, where participants used the application while engaging in actual sightseeing. The results demonstrated that IEL curves based on five- and ten-point evaluations exhibited stronger alignment with the EDA data than those based on a three-point evaluation. In particular, the inclusion of negative evaluations on a ten-point scale enabled a more comprehensive representation of emotional fluctuations. These findings suggest that the proposed method enhances the expressive capacity for emotional self-reporting and supports the practical implementation of data-driven tourism route planning.