Abstract
User Experience is an increasingly critical factor in product success. This study evaluates a new method that uses emotion detection software to capture the emotional data of users in real time while performing specific tasks within an app, and explores how this new method can complement traditional user experience methods such as questionnaires. Our study included N = 200 who were asked to complete three tasks within a health test app while emotion data was captured using the integrated emotion detection software. Results when clustering these emotion data show that the user experience acquired in the task is consistent with the emotion data valence. In addition, we found that a user emotion profile can be established to better characterize user experience of the participants during each task. This may help designers to better target users and product design.
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Acknowledgments
This research is supported by UXLab of school of arts and media of Tongji university. We would like to express our gratitude to: Yujia Wang, Huiyan Chen, Ziwei Qian, Chaojie Wang, and Cuiqiong Cheng.
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Appendix
The emotion state and detailed description of each user in each task.
In the scatter plot, each point represents the mean of a kind of a control in task one of all users. At the same time, the bar graph corresponds to the user experience questionnaire and represents the number of users selecting each option.
In the scatter plot, each point represents the mean of a kind of a control in task two of all users. At the same time, the bar graph corresponds to the user experience questionnaire and represents the number of users selecting each option.
In the scatter plot, each point represents the mean of a kind of a control in task three of all users. At the same time, the bar graph corresponds to the user experience questionnaire and represents the number of users selecting each option.
User emotion profile
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Chen, Y., You, F., Wang, J., Schroeter, R. (2018). Measuring User Experience in Situ: Use Emotion Data to Assess User Experience. In: Ahram, T., Falcão, C. (eds) Advances in Usability and User Experience. AHFE 2017. Advances in Intelligent Systems and Computing, vol 607. Springer, Cham. https://doi.org/10.1007/978-3-319-60492-3_52
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DOI: https://doi.org/10.1007/978-3-319-60492-3_52
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