Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach

The number of consumers playing virtual reality games is booming. To speed up product iteration, the user experience team needs to collect and analyze unsatisfying experiences in time. In this paper, we aim to detect the unsatisfying experiences hidden in online reviews of virtual reality exergames...

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Autores principales:	Xiaoyan Zhang, Qiang Yan, Simin Zhou, Linye Ma, Siran Wang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	virtual reality exergame user experience online reviews Information technology T58.5-58.64
Acceso en línea:	https://doaj.org/article/94c3ef58a432420c8c13b1fd7a56cd69
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id	oai:doaj.org-article:94c3ef58a432420c8c13b1fd7a56cd69
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spelling	oai:doaj.org-article:94c3ef58a432420c8c13b1fd7a56cd692021-11-25T17:58:45ZAnalysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach10.3390/info121104862078-2489https://doaj.org/article/94c3ef58a432420c8c13b1fd7a56cd692021-11-01T00:00:00Zhttps://www.mdpi.com/2078-2489/12/11/486https://doaj.org/toc/2078-2489The number of consumers playing virtual reality games is booming. To speed up product iteration, the user experience team needs to collect and analyze unsatisfying experiences in time. In this paper, we aim to detect the unsatisfying experiences hidden in online reviews of virtual reality exergames using a deep learning method and find out the unmet psychological needs of users based on self-determination theory. Convolutional neural networks for sentence classification (textCNN) are used in this study to classify online reviews with unsatisfying experiences. For comparison, we set eXtreme gradient boosting (XGBoost) with lexical features as the baseline of machine learning. Term frequency-inverse document frequency (TF-IDF) is used to extract keywords from every set of classified reviews. The micro-F1 score of textCNN classifier is 90.00, which is better than 82.69 of XGBoost. The top 10 keywords of every set of reviews reflect relevant topics of unmet psychological needs. This paper explores the potential problems causing unsatisfying experiences and unmet psychological needs in virtual reality exergames through text mining and makes a supplement for experimental studies about virtual reality exergames.Xiaoyan ZhangQiang YanSimin ZhouLinye MaSiran WangMDPI AGarticlevirtual realityexergameuser experienceonline reviewsInformation technologyT58.5-58.64ENInformation, Vol 12, Iss 486, p 486 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	virtual reality exergame user experience online reviews Information technology T58.5-58.64
spellingShingle	virtual reality exergame user experience online reviews Information technology T58.5-58.64 Xiaoyan Zhang Qiang Yan Simin Zhou Linye Ma Siran Wang Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach
description	The number of consumers playing virtual reality games is booming. To speed up product iteration, the user experience team needs to collect and analyze unsatisfying experiences in time. In this paper, we aim to detect the unsatisfying experiences hidden in online reviews of virtual reality exergames using a deep learning method and find out the unmet psychological needs of users based on self-determination theory. Convolutional neural networks for sentence classification (textCNN) are used in this study to classify online reviews with unsatisfying experiences. For comparison, we set eXtreme gradient boosting (XGBoost) with lexical features as the baseline of machine learning. Term frequency-inverse document frequency (TF-IDF) is used to extract keywords from every set of classified reviews. The micro-F1 score of textCNN classifier is 90.00, which is better than 82.69 of XGBoost. The top 10 keywords of every set of reviews reflect relevant topics of unmet psychological needs. This paper explores the potential problems causing unsatisfying experiences and unmet psychological needs in virtual reality exergames through text mining and makes a supplement for experimental studies about virtual reality exergames.
format	article
author	Xiaoyan Zhang Qiang Yan Simin Zhou Linye Ma Siran Wang
author_facet	Xiaoyan Zhang Qiang Yan Simin Zhou Linye Ma Siran Wang
author_sort	Xiaoyan Zhang
title	Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach
title_short	Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach
title_full	Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach
title_fullStr	Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach
title_full_unstemmed	Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach
title_sort	analysis of unsatisfying user experiences and unmet psychological needs for virtual reality exergames using deep learning approach
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/94c3ef58a432420c8c13b1fd7a56cd69
work_keys_str_mv	AT xiaoyanzhang analysisofunsatisfyinguserexperiencesandunmetpsychologicalneedsforvirtualrealityexergamesusingdeeplearningapproach AT qiangyan analysisofunsatisfyinguserexperiencesandunmetpsychologicalneedsforvirtualrealityexergamesusingdeeplearningapproach AT siminzhou analysisofunsatisfyinguserexperiencesandunmetpsychologicalneedsforvirtualrealityexergamesusingdeeplearningapproach AT linyema analysisofunsatisfyinguserexperiencesandunmetpsychologicalneedsforvirtualrealityexergamesusingdeeplearningapproach AT siranwang analysisofunsatisfyinguserexperiencesandunmetpsychologicalneedsforvirtualrealityexergamesusingdeeplearningapproach
_version_	1718411760526950400

Analysis of Unsatisfying User Experiences and Unmet Psychological Needs for Virtual Reality Exergames Using Deep Learning Approach

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