A dataset of interactions and emotions for website user experience evaluation

This dataset is designed for affective computing applications in the context of human-computer interaction, with a particular focus on user experience (UX) and website interactions. The dataset comprises interaction logs, including mouse movements and key presses, collected over a period of thirty days from various websites. Each recorded interaction is paired with corresponding emotional data, which is encoded according to Ekman’s emotion model, allowing for a nuanced analysis of emotional responses. This dataset is particularly valuable for examining how emotions influence user behaviour across different types of websites, as well as identifying patterns and trends in website interactions. The primary aim of this dataset is to facilitate the development of non-intrusive AI systems capable of detecting user emotions solely based on interaction data. Such systems have potential applications in improving UX design, personalizing web content, and enhancing the overall user experience by adapting to emotional states without requiring explicit input from users.