Influence of household virtual reality products on emotions during the COVID-19 pandemic: a semantic network analysis

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Publié dans:Humanities & Social Sciences Communications vol. 12, no. 1 (Dec 2025), p. 309
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Springer Nature B.V.
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245 1 |a Influence of household virtual reality products on emotions during the COVID-19 pandemic: a semantic network analysis 
260 |b Springer Nature B.V.  |c Dec 2025 
513 |a Journal Article 
520 3 |a This study aimed to explore the emotional effects of virtual reality (VR) products during the COVID-19 pandemic by analyzing user comments of VR and COVID-19 on Steam platforms and uncovering the association between emotions and themes, and trends in emotional expression. A total of 1249 valid English-language content data were collected from January 1, 2020 to December 31, 2022 on the Steam platform, by searching for VR- and COVID-19-related keywords. Emotion analysis was used to encode each user comments. Semantic network analysis and a clustering algorithm were used to mine the potential semantic relationship between different topics and sentiments in the content. The changes and trends of topics and sentiments in each time period were analyzed. The findings indicate that during COVID-19, users were more likely to express anticipation and trust in VR products than they were to complain about COVID19. The use of VR devices is one of the sources of positive emotions during the COVID-19 pandemic. Promoting the use of metaverse social products, such as VR, in major health and pandemic prevention events may be beneficial for fostering positive emotions. The proposed framework of semantic networks and sentiment analysis is also a theoretical contribution. This study reveals the complex relationship between emotional changes and VR usage scenarios, further expanding the theoretical framework of virtual reality in social interaction and emotional regulation. From a policy perspective, governments and public health organizations should recognize the emotional support functions of VR technology during social crises. 
610 4 |a Cambridge University Press Oxford University Press World Health Organization 
653 |a Emotions 
653 |a Coronaviruses 
653 |a Virtual reality 
653 |a COVID-19 
653 |a Network analysis 
653 |a Public health 
653 |a Language usage 
653 |a Emotional support 
653 |a Semantic analysis 
653 |a Health care industry 
653 |a Self control 
653 |a Facial expressions 
653 |a Sentiment analysis 
653 |a Pandemics 
653 |a Semantic processing 
653 |a Clustering 
653 |a Social interaction 
653 |a Health services 
653 |a Self expression 
653 |a English language 
653 |a Sociolinguistics 
653 |a Semantic networks 
653 |a Emotional regulation 
653 |a Positive emotions 
653 |a Theoretical linguistics 
773 0 |t Humanities & Social Sciences Communications  |g vol. 12, no. 1 (Dec 2025), p. 309 
786 0 |d ProQuest  |t Social Science Database 
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