Exploring approaches to compare emotional responses to the same stimuli from different individuals

Understand human emotional behavior is a challenging yet crucial endeavor for enhancing user experience through the application of Affective Computing techniques. These methods have the potential to foster more natural and emotionally responsive interactions between users and systems. In a multicultural world, it is equally important to understand the varied emotional responses individuals have to a same stimuli, ensuring that software adaptations and interventions are appropriately tailored. This study examines two methodologies for comparing how individuals from diverse backgrounds react emotionally to the two audiovisual stimulus. By utilizing data analysis and machine learning tools, the study aims to explore whether two individuals react similarly to a same stimulus. Alongside an exploration of the unique features of each approach, the research validates these methods by analyzing the emotional responses of 39 participants, identifying both commonalities and differences. The findings not only underscore the approaches' effectiveness but also highlight their potential for complementing one another.