Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews
The accelerating pace of digital life has intensified psychological strain, increasing the demand for accessible and systematized emotional support tools. Relaxing video games—defined as low-pressure, non-competitive games designed to promote calm and emotional relief—offer immersive environments th...
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MDPI AG
2025-07-01
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| Series: | Systems |
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| author | Yuxin Xing Wenbao Ma Qiang You Jiaxing Li |
| author_facet | Yuxin Xing Wenbao Ma Qiang You Jiaxing Li |
| author_sort | Yuxin Xing |
| collection | DOAJ |
| description | The accelerating pace of digital life has intensified psychological strain, increasing the demand for accessible and systematized emotional support tools. Relaxing video games—defined as low-pressure, non-competitive games designed to promote calm and emotional relief—offer immersive environments that facilitate affective engagement and sustained user involvement. This study proposes a computational framework that integrates sentiment analysis and topic modeling to investigate the affective mechanisms and behavioral dynamics associated with relaxing gameplay. We analyzed nearly 60,000 user reviews from the Steam platform in both English and Chinese, employing a hybrid methodology that combines sentiment classification, dual-stage Latent Dirichlet Allocation (LDA), and multi-label mechanism tagging. Emotional relief emerged as the dominant sentiment (62.8%), whereas anxiety was less prevalent (10.4%). Topic modeling revealed key affective dimensions such as pastoral immersion and cozy routine. Regression analysis demonstrated that mechanisms like emotional relief (β = 0.0461, <i>p</i> = 0.001) and escapism (β = 0.1820, <i>p</i> < 0.001) were significant predictors of longer playtime, while Anxiety Expression lost statistical significance (<i>p</i> = 0.124) when contextual controls were added. The findings highlight the potential of relaxing video games as scalable emotional regulation tools and demonstrate how sentiment- and topic-driven modeling can support system-level understanding of affective user behavior. This research contributes to affective computing, digital mental health, and the design of emotionally aware interactive systems. |
| format | Article |
| id | doaj-art-59c26455c9c8484584baa806afcf04fe |
| institution | Kabale University |
| issn | 2079-8954 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Systems |
| spelling | doaj-art-59c26455c9c8484584baa806afcf04fe2025-08-20T03:32:18ZengMDPI AGSystems2079-89542025-07-0113754010.3390/systems13070540Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User ReviewsYuxin Xing0Wenbao Ma1Qiang You2Jiaxing Li3School of Humanities and Social Science, Xi’an Jiaotong University, 28 Xianning West Road, Xi’an 710049, ChinaSchool of Humanities and Social Science, Xi’an Jiaotong University, 28 Xianning West Road, Xi’an 710049, ChinaCollege of Design and Engineering, National University of Singapore, 3 Engineering Drive 2, Singapore 117578, SingaporeSchool of Humanities and Social Science, Xi’an Jiaotong University, 28 Xianning West Road, Xi’an 710049, ChinaThe accelerating pace of digital life has intensified psychological strain, increasing the demand for accessible and systematized emotional support tools. Relaxing video games—defined as low-pressure, non-competitive games designed to promote calm and emotional relief—offer immersive environments that facilitate affective engagement and sustained user involvement. This study proposes a computational framework that integrates sentiment analysis and topic modeling to investigate the affective mechanisms and behavioral dynamics associated with relaxing gameplay. We analyzed nearly 60,000 user reviews from the Steam platform in both English and Chinese, employing a hybrid methodology that combines sentiment classification, dual-stage Latent Dirichlet Allocation (LDA), and multi-label mechanism tagging. Emotional relief emerged as the dominant sentiment (62.8%), whereas anxiety was less prevalent (10.4%). Topic modeling revealed key affective dimensions such as pastoral immersion and cozy routine. Regression analysis demonstrated that mechanisms like emotional relief (β = 0.0461, <i>p</i> = 0.001) and escapism (β = 0.1820, <i>p</i> < 0.001) were significant predictors of longer playtime, while Anxiety Expression lost statistical significance (<i>p</i> = 0.124) when contextual controls were added. The findings highlight the potential of relaxing video games as scalable emotional regulation tools and demonstrate how sentiment- and topic-driven modeling can support system-level understanding of affective user behavior. This research contributes to affective computing, digital mental health, and the design of emotionally aware interactive systems.https://www.mdpi.com/2079-8954/13/7/540sentiment analysistopic modelingvideo gamesuser-generated contentemotional regulationbehavioral dynamics |
| spellingShingle | Yuxin Xing Wenbao Ma Qiang You Jiaxing Li Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews Systems sentiment analysis topic modeling video games user-generated content emotional regulation behavioral dynamics |
| title | Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews |
| title_full | Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews |
| title_fullStr | Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews |
| title_full_unstemmed | Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews |
| title_short | Modeling Affective Mechanisms in Relaxing Video Games: Sentiment and Topic Analysis of User Reviews |
| title_sort | modeling affective mechanisms in relaxing video games sentiment and topic analysis of user reviews |
| topic | sentiment analysis topic modeling video games user-generated content emotional regulation behavioral dynamics |
| url | https://www.mdpi.com/2079-8954/13/7/540 |
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