DUX: a dataset of user interactions and user emotions

Dominick Leppich

Carina Bieber

Katrin Proschek

Patrick Harms

Ulf Schubert

User experience evaluation is becoming increasingly important, and so is emotion recognition. Recognizing users’ emotions based on their interactions alone would not be intrusive to users and can be implemented in many applications. This is still an area of active research and requires data containing both the user interactions and the corresponding emotions. Currently, there is no public dataset for emotion recognition from keystroke, mouse and touchscreen dynamics. We have created such a dataset for keyboard and mouse interactions through a dedicated user study and made it publicly available for other researchers. This paper examines our study design and the process of creating the dataset. We conducted the study using a test application for travel expense reports with 50 participants. We want to be able to detect predominantly negative emotions, so we added emotional triggers to our test application. However, further research is needed to determine the relationship between user interactions and emotions.

This publication uses Facial Expression Analysis which is fully integrated into iMotions Lab

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