uxSense: Supporting User Experience Analysis with Visualization and Computer Vision

Analyzing user behavior from usability evaluation can be a challenging and time-consuming task, especially as the number of participants and the scale and complexity of the evaluation grows. We propose uxSense, a visual analytics system using machine learning methods to extract user behavior from au...

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Bibliographic Details
Published in:arXiv.org
Main Authors: Batch, Andrea, Ji, Yipeng, Fan, Mingming, Zhao, Jian, Elmqvist, Niklas
Format: Paper
Language:English
Published: Ithaca Cornell University Library, arXiv.org 11.10.2023
Subjects:
Audio data
Computer vision
Data transmission
Machine learning
Natural language processing
Pattern recognition
User experience
ISSN:2331-8422
Online Access:Get full text
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Summary:Analyzing user behavior from usability evaluation can be a challenging and time-consuming task, especially as the number of participants and the scale and complexity of the evaluation grows. We propose uxSense, a visual analytics system using machine learning methods to extract user behavior from audio and video recordings as parallel time-stamped data streams. Our implementation draws on pattern recognition, computer vision, natural language processing, and machine learning to extract user sentiment, actions, posture, spoken words, and other features from such recordings. These streams are visualized as parallel timelines in a web-based front-end, enabling the researcher to search, filter, and annotate data across time and space. We present the results of a user study involving professional UX researchers evaluating user data using uxSense. In fact, we used uxSense itself to evaluate their sessions.
Bibliography:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
ISSN:2331-8422
DOI:10.48550/arxiv.2310.07300