Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101028
A. Marthe Möller , Joanna Strycharz
The past decades have seen a rise in scholarly interest in the concept of eudaimonic entertainment experiences, resulting in multiple conceptualizations of the term. Recently, one such experience is Kama Muta (“moved by love”), which is typically measured through self-reports. However, it remains unclear to what extent Kama Muta is reflected in individuals’ spontaneous reactions to media content. This study examines viewers’ spontaneous responses to online videos (e.g., likes, comments) and compares these to their self-reported experiences of Kama Muta. Results show that viewers’ experiences of Kama Muta are mostly unrelated to the number of reactions that they post. Furthermore, topic modeling shows that Kama Muta is reflected in viewers’ comments to a limited extent. We conclude that making computational methods sufficiently efficient to detect abstract constructs such as Kama Muta in short texts requires additional methodological advancements.
{"title":"Searching for traces of Kama Muta: Examining viewers’ responses to online videos","authors":"A. Marthe Möller , Joanna Strycharz","doi":"10.1016/j.entcom.2025.101028","DOIUrl":"10.1016/j.entcom.2025.101028","url":null,"abstract":"<div><div>The past decades have seen a rise in scholarly interest in the concept of eudaimonic entertainment experiences, resulting in multiple conceptualizations of the term. Recently, one such experience is Kama Muta (“moved by love”), which is typically measured through self-reports. However, it remains unclear to what extent Kama Muta is reflected in individuals’ spontaneous reactions to media content. This study examines viewers’ spontaneous responses to online videos (e.g., likes, comments) and compares these to their self-reported experiences of Kama Muta. Results show that viewers’ experiences of Kama Muta are mostly unrelated to the number of reactions that they post. Furthermore, topic modeling shows that Kama Muta is reflected in viewers’ comments to a limited extent. We conclude that making computational methods sufficiently efficient to detect abstract constructs such as Kama Muta in short texts requires additional methodological advancements.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101028"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101024
Li Li , Zhimin Niu , Xi Gong , Zhiyu Pi , Songli Mei , Mark D. Griffiths
During the COVID-19 pandemic, many scholars in the field of behavioral addiction examined the risk of gaming disorder (GD). The association between GD, depression, social anxiety, and risk perception toward COVID-19 among Chinese university students has remained largely uninvestigated, especially using network analysis. Therefore, the present study (N = 1794) examined the relationship between these variables during the pandemic using Gaussian graphical model (GGM) and Moderated Network Model (MNM) approaches. In the GGM and MNM, GD had a significant interaction with depression. Individual risk perception and public risk perception had stronger connections in the network, as did depression and social anxiety. In addition, ‘fatigue’ was identified as the core symptom of depression. Neither moderation effects (i.e., three-way interaction between GD, depression, social anxiety, and risk perception) nor gender differences in network comparisons were found. These results suggest that relieving negative emotional states may have helped prevent GD during the COVID-19 pandemic, while the influence of risk perception on GD and negative emotions needs to be further examined.
{"title":"Gaming disorder and its association with depression, social anxiety, and risk perception during the COVID-19 pandemic: A study using a Gaussian graphical model and moderated network models","authors":"Li Li , Zhimin Niu , Xi Gong , Zhiyu Pi , Songli Mei , Mark D. Griffiths","doi":"10.1016/j.entcom.2025.101024","DOIUrl":"10.1016/j.entcom.2025.101024","url":null,"abstract":"<div><div>During the COVID-19 pandemic, many scholars in the field of behavioral addiction examined the risk of gaming disorder (GD). The association between GD, depression, social anxiety, and risk perception toward COVID-19 among Chinese university students has remained largely uninvestigated, especially using network analysis. Therefore, the present study (N = 1794) examined the relationship between these variables during the pandemic using Gaussian graphical model (GGM) and Moderated Network Model (MNM) approaches. In the GGM and MNM, GD had a significant interaction with depression. Individual risk perception and public risk perception had stronger connections in the network, as did depression and social anxiety. In addition, ‘fatigue’ was identified as the core symptom of depression. Neither moderation effects (i.e., three-way interaction between GD, depression, social anxiety, and risk perception) nor gender differences in network comparisons were found. These results suggest that relieving negative emotional states may have helped prevent GD during the COVID-19 pandemic, while the influence of risk perception on GD and negative emotions needs to be further examined.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101024"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145219293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101055
Saif Alatrash , Sylvester Arnab , Kaja Antlej
Entertainment plays a pivotal role in capturing attention and encouraging self-involvement, enhancing the appeal of experiences through engaging practices like storytelling and game-based activities. This paper investigates the impact of gamification elements on user experience, with a focus on how users perceive interaction, immersion, and learning when these elements are integrated into virtual reality (VR) environments in museum settings. Two versions of a gamified VR experience were developed using the Unreal Engine (UE) 3D computer graphic game engine to ensure high fidelity and presence for end users through real-time simulation. The first version was tested at the Transport Museum in Coventry, UK, providing insights into the improvements to be made to better address the interaction, immersion, and learning aspects. The second refined version was deployed in Geelong and Melbourne, Australia. A quantitative approach was used to compare the two experiences using the mean and significance between items. The findings show a significant improvement in user experience in the second gamified experience in Australia. The enhanced gamified elements promoted motivation and intuitive navigation with minimal game inputs, improving user interaction and concentration while reducing external distractions. The results indicate a notable difference between the two experiences in terms of interaction and immersion, with the simplified inputs in the second experience significantly enhancing usability during VR navigation. Overall, the second experience was more effective than the first regarding mechanics, inputs, and guidance. These results underscore the importance of avoiding complexity and facilitating intuitive interaction when designing gamified experiences.
{"title":"Gamifying Museum Exploration: A Virtual Reality Approach to Enhancing Visitor Engagement","authors":"Saif Alatrash , Sylvester Arnab , Kaja Antlej","doi":"10.1016/j.entcom.2025.101055","DOIUrl":"10.1016/j.entcom.2025.101055","url":null,"abstract":"<div><div>Entertainment plays a pivotal role in capturing attention and encouraging self-involvement, enhancing the appeal of experiences through engaging practices like storytelling and game-based activities. This paper investigates the impact of gamification elements on user experience, with a focus on how users perceive interaction, immersion, and learning when these elements are integrated into virtual reality (VR) environments in museum settings. Two versions of a gamified VR experience were developed using the Unreal Engine (UE) 3D computer graphic game engine to ensure high fidelity and presence for end users through real-time simulation. The first version was tested at the Transport Museum in Coventry, UK, providing insights into the improvements to be made to better address the interaction, immersion, and learning aspects. The second refined version was deployed in Geelong and Melbourne, Australia. A quantitative approach was used to compare the two experiences using the mean and significance between items. The findings show a significant improvement in user experience in the second gamified experience in Australia. The enhanced gamified elements promoted motivation and intuitive navigation with minimal game inputs, improving user interaction and concentration while reducing external distractions. The results indicate a notable difference between the two experiences in terms of interaction and immersion, with the simplified inputs in the second experience significantly enhancing usability during VR navigation. Overall, the second experience was more effective than the first regarding mechanics, inputs, and guidance. These results underscore the importance of avoiding complexity and facilitating intuitive interaction when designing gamified experiences.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101055"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101050
Lijuan Cui , Yaming Wei
This study explores how the cross-media creative trajectory of Robert Schumann’s piano suite Papillons (Op. 2) can be extended through an emotion-driven AI model. Drawing on The Masked-Ball chapter from Jean Paul’s novel Flegeljahre, we applied natural language processing techniques to extract four-dimensional emotion vectors (joy, sadness, anger, optimism) from selected literary segments. These vectors were paired with the first ten movements of Papillons to train two Long Short-Term Memory (LSTM) network. We then used the emotional profile of the novel’s final, musically unrepresented passages as input to generate an eleventh piano movement that preserves stylistic coherence and structural consistency. The results validate the technical feasibility of a “text–emotion–music” transformation pathway and demonstrate the potential of AI in simulating cross-media creativity. As a pilot study, this work provides preliminary evidence for emotion-guided music generation and offers a conceptual and methodological foundation for future multimodal generative models and human–AI co-creative systems.
{"title":"Schumann’s Papillons reimagined through emotion-driven LSTM composition: A pilot study","authors":"Lijuan Cui , Yaming Wei","doi":"10.1016/j.entcom.2025.101050","DOIUrl":"10.1016/j.entcom.2025.101050","url":null,"abstract":"<div><div>This study explores how the cross-media creative trajectory of Robert Schumann’s piano suite <em>Papillons (Op. 2)</em> can be extended through an emotion-driven AI model. Drawing on <em>The Masked-Ball</em> chapter from Jean Paul’s novel <em>Flegeljahre</em>, we applied natural language processing techniques to extract four-dimensional emotion vectors (joy, sadness, anger, optimism) from selected literary segments. These vectors were paired with the first ten movements of <em>Papillon</em>s to train two Long Short-Term Memory (LSTM) network. We then used the emotional profile of the novel’s final, musically unrepresented passages as input to generate an eleventh piano movement that preserves stylistic coherence and structural consistency. The results validate the technical feasibility of a “text–emotion–music” transformation pathway and demonstrate the potential of AI in simulating cross-media creativity. As a pilot study, this work provides preliminary evidence for emotion-guided music generation and offers a conceptual and methodological foundation for future multimodal generative models and human–AI co-creative systems.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101050"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101048
Tibor Guzsvinecz
The concept of liminal spaces has gained increasing attention in recent years, both in digital culture and academic discourse. Video games have also embraced this concept, with some developers creating immersive digital environments that evoke feelings of liminality. This study explores player experiences and emotions associated with “games of liminality” as it focuses on video games that place players in transitional, ambiguous spaces. Using text mining and sentiment analysis techniques, 66,858 reviews from the Steam platform were analyzed to identify emotional responses and recurring themes. The study identified anticipation, trust, and joy as the most frequently evoked emotions, while fear and surprise were also common, mainly in games incorporating horror elements. The analysis revealed significant differences between positive and negative reviews, with negative reviews tending to be more detailed and critical. Additionally, the Backrooms phenomenon was shown to influence player perceptions and contribute to the growing cultural fascination with liminal spaces. The results provide a deeper understanding of how players engage emotionally with liminal space games that can be used by developers to enhance game design to optimize immersive experiences and support further research into the psychological impact of digital environments on players.
{"title":"Reactions to video games that evoke a feeling of liminality","authors":"Tibor Guzsvinecz","doi":"10.1016/j.entcom.2025.101048","DOIUrl":"10.1016/j.entcom.2025.101048","url":null,"abstract":"<div><div>The concept of liminal spaces has gained increasing attention in recent years, both in digital culture and academic discourse. Video games have also embraced this concept, with some developers creating immersive digital environments that evoke feelings of liminality. This study explores player experiences and emotions associated with “games of liminality” as it focuses on video games that place players in transitional, ambiguous spaces. Using text mining and sentiment analysis techniques, 66,858 reviews from the Steam platform were analyzed to identify emotional responses and recurring themes. The study identified anticipation, trust, and joy as the most frequently evoked emotions, while fear and surprise were also common, mainly in games incorporating horror elements. The analysis revealed significant differences between positive and negative reviews, with negative reviews tending to be more detailed and critical. Additionally, the Backrooms phenomenon was shown to influence player perceptions and contribute to the growing cultural fascination with liminal spaces. The results provide a deeper understanding of how players engage emotionally with liminal space games that can be used by developers to enhance game design to optimize immersive experiences and support further research into the psychological impact of digital environments on players.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101048"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101034
Yi-Chun Li , Wen-Huei Chou , Yen-Liang Wu
This study explores the application of Augmented Reality (AR) in enhancing navigation and visitor engagement at the Chiayi Sawmill in Taiwan. Using the Extended Technology Acceptance Model (ETAM), which integrates TAM2 and UTAUT, the study assesses user acceptance and factors influencing AR navigation adoption in outdoor cultural heritage sites. Data were collected from 80 visitors using AR-guided tours. Results indicate that perceived playfulness strongly affects behavioral intention, while perceived usefulness influences user attitudes, showing that visitors value both the informative content and the interactive experience. A positive user experience was found to enhance perceived ease of use, which in turn promotes acceptance of the AR system. However, the study also reveals that enjoyment of the AR content is more dependent on the system’s design than on the user’s prior experience. The findings validate the ETAM in outdoor heritage navigation, offering practical insights for AR application in cultural heritage, emphasizing the importance of optimizing user experience, system design, and playfulness to increase visitor satisfaction and engagement. This study contributes to extending AR research from indoor settings to outdoor cultural sites and provides a reference for future AR navigation design in cultural heritage settings.
{"title":"Exploring the technological experience and impact assessment of Augmented Reality in outdoor cultural heritage guided tours: A case study of the Chiayi Sawmill","authors":"Yi-Chun Li , Wen-Huei Chou , Yen-Liang Wu","doi":"10.1016/j.entcom.2025.101034","DOIUrl":"10.1016/j.entcom.2025.101034","url":null,"abstract":"<div><div>This study explores the application of Augmented Reality (AR) in enhancing navigation and visitor engagement at the Chiayi Sawmill in Taiwan. Using the Extended Technology Acceptance Model (ETAM), which integrates TAM2 and UTAUT, the study assesses user acceptance and factors influencing AR navigation adoption in outdoor cultural heritage sites. Data were collected from 80 visitors using AR-guided tours. Results indicate that perceived playfulness strongly affects behavioral intention, while perceived usefulness influences user attitudes, showing that visitors value both the informative content and the interactive experience. A positive user experience was found to enhance perceived ease of use, which in turn promotes acceptance of the AR system. However, the study also reveals that enjoyment of the AR content is more dependent on the system’s design than on the user’s prior experience. The findings validate the ETAM in outdoor heritage navigation, offering practical insights for AR application in cultural heritage, emphasizing the importance of optimizing user experience, system design, and playfulness to increase visitor satisfaction and engagement. This study contributes to extending AR research from indoor settings to outdoor cultural sites and provides a reference for future AR navigation design in cultural heritage settings.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101034"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101027
Silvia García-Méndez, Francisco de Arriba-Pérez
The increasing number of spectators and players in e-sports, along with the development of optimized communication solutions and cloud computing technology, has motivated the constant growth of the online game industry. Even though Artificial Intelligence-based solutions for e-sports analytics are traditionally defined as extracting meaningful patterns from related data and visualizing them to enhance decision-making, most of the effort in professional winning prediction has been focused on the classification aspect from a batch perspective, also leaving aside the visualization techniques. Consequently, this work contributes to an explainable win prediction classification solution in streaming in which input data is controlled over several sliding windows to reflect relevant game changes. Experimental results attained an accuracy higher than 90%, surpassing the performance of competing solutions in the literature. Ultimately, our system can be leveraged by ranking and recommender systems for informed decision-making, thanks to the explainability module, which fosters trust in the outcome predictions.
{"title":"Explainable e-sports win prediction through Machine Learning classification in streaming","authors":"Silvia García-Méndez, Francisco de Arriba-Pérez","doi":"10.1016/j.entcom.2025.101027","DOIUrl":"10.1016/j.entcom.2025.101027","url":null,"abstract":"<div><div>The increasing number of spectators and players in e-sports, along with the development of optimized communication solutions and cloud computing technology, has motivated the constant growth of the online game industry. Even though Artificial Intelligence-based solutions for e-sports analytics are traditionally defined as extracting meaningful patterns from related data and visualizing them to enhance decision-making, most of the effort in professional winning prediction has been focused on the classification aspect from a batch perspective, also leaving aside the visualization techniques. Consequently, this work contributes to an explainable win prediction classification solution in streaming in which input data is controlled over several sliding windows to reflect relevant game changes. Experimental results attained an accuracy higher than 90%, surpassing the performance of competing solutions in the literature. Ultimately, our system can be leveraged by ranking and recommender systems for informed decision-making, thanks to the explainability module, which fosters trust in the outcome predictions.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101027"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101032
A. Balamurugan , Sudeep Varshney , K. Raghuveer , M.Kishore Kumar , Siddharth Misra , M.Ramkumar Prabhu
In the age of rapidly growing digital entertainment through video games, understanding their impact on students and identifying related factors is crucial for educational and developmental considerations. Video game use has an influence on social conduct, academic achievement, and general well-being in addition to being merely amusing. The study’s aim is to provide insights into the intricate nature of video game engagement among the demographic by examining variables like social media usage, parental involvement, and device ownership. To determine the extent to students use video games and factors influence their gaming habits. The study utilized a Video Game Addiction Scale alongside a comprehensive survey. Participants were extended to 200 students enrolled in 8th and 9th grades across multiple schools to participate in the survey. To explore relationships and associations among variables, statistical analyses are conducted, such as inferential tests and descriptive statistics. The findings provide insight into potential variables that might influence both positive and negative features of video game participation. Participants can develop an environment that motivates students to play video games responsibly and in a balanced manner by acknowledging the complexity of the elements that influence gaming behaviour.
{"title":"The playful chronicles: investigating adolescents’ video game engagement with an entertainment flair","authors":"A. Balamurugan , Sudeep Varshney , K. Raghuveer , M.Kishore Kumar , Siddharth Misra , M.Ramkumar Prabhu","doi":"10.1016/j.entcom.2025.101032","DOIUrl":"10.1016/j.entcom.2025.101032","url":null,"abstract":"<div><div>In the age of rapidly growing digital entertainment through video games, understanding their impact on students and identifying related factors is crucial for educational and developmental considerations. Video game use has an influence on social conduct, academic achievement, and general well-being in addition to being merely amusing. The study’s aim is to provide insights into the intricate nature of video game engagement among the demographic by examining variables like social media usage, parental involvement, and device ownership. To determine the extent to students use video games and factors influence their gaming habits. The study utilized a Video Game Addiction Scale alongside a comprehensive survey. Participants were extended to 200 students enrolled in 8th and 9th grades across multiple schools to participate in the survey. To explore relationships and associations among variables, statistical analyses are conducted, such as inferential tests and descriptive statistics. The findings provide insight into potential variables that might influence both positive and negative features of video game participation. Participants can develop an environment that motivates students to play video games responsibly and in a balanced manner by acknowledging the complexity of the elements that influence gaming behaviour.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101032"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101017
Guiquan Huo , Xiao Liu , Tingting Chen
Predicting the fitness of athletes is important for improving their performance over time. Training sessions and past performance records are the common features used to guide athletes’ gradual improvement. This study integrates conventional deep learning and partial fuzzy TOPSIS to assess athletes’ physical fitness and performance. First, the learning process identifies the precise demands needed for ongoing improvement through optimized training. The model regularly checks whether the training inputs meet the evolving needs of different sessions. These identified inputs are further validated using the fuzzy TOPSIS method to determine a clear pathway for sustained, reliable performance gains. The prioritized results produced over multiple iterations are useful in identifying highly effective fitness programs that support steady improvement. The proposed method is evaluated using the Wushu training requirements dataset to identify specific training needs and performance outcomes based on multiple practice sessions.
{"title":"Prediction of physical fitness and performance of Wushus athletes based on machine learning and fuzzy TOPSIS method","authors":"Guiquan Huo , Xiao Liu , Tingting Chen","doi":"10.1016/j.entcom.2025.101017","DOIUrl":"10.1016/j.entcom.2025.101017","url":null,"abstract":"<div><div>Predicting the fitness of athletes is important for improving their performance over time. Training sessions and past performance records are the common features used to guide athletes’ gradual improvement. This study integrates conventional deep learning and partial fuzzy TOPSIS to assess athletes’ physical fitness and performance. First, the learning process identifies the precise demands needed for ongoing improvement through optimized training. The model regularly checks whether the training inputs meet the evolving needs of different sessions. These identified inputs are further validated using the fuzzy TOPSIS method to determine a clear pathway for sustained, reliable performance gains. The prioritized results produced over multiple iterations are useful in identifying highly effective fitness programs that support steady improvement. The proposed method is evaluated using the Wushu training requirements dataset to identify specific training needs and performance outcomes based on multiple practice sessions.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101017"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145094858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.1016/j.entcom.2025.101029
Yanze Liu , Tian-Hui You , Junrong Zou , Yuan Yuan , Bing-Bing Cao
The rapid expansion of the video game market intensifies customers’ difficulty in selecting preference-aligned games. Although online reviews offer valuable insights, effectively leveraging this information remains challenging. To address this, we propose S-Kano-TOPSIS, a personalized ranking method for video games that integrates requirement categories and public opinion. First, BERTopic is used to extract customer requirements (CRs), and their performance is evaluated via sentiment analysis using a BW-CNN model. Then, SHAP is applied to quantify the influence of each CR on customer satisfaction. The Kano model is employed to adjust CR importance based on their influence patterns. Furthermore, to reflect real-world decision-making, we incorporate preference similarity by analyzing reviews of games similar to those the customer has played. Finally, TOPSIS is used to generate rankings tailored to individual needs. Experiments on 72,000 reviews from eight video games demonstrate that the proposed method surpasses baseline approaches across multiple evaluation metrics. These results suggest that S-Kano-TOPSIS offers a structured and quantifiable approach to personalized video game ranking.
{"title":"Personalized ranking for video games based on online reviews: An S-Kano-TOPSIS method integrating requirement categories and public opinion","authors":"Yanze Liu , Tian-Hui You , Junrong Zou , Yuan Yuan , Bing-Bing Cao","doi":"10.1016/j.entcom.2025.101029","DOIUrl":"10.1016/j.entcom.2025.101029","url":null,"abstract":"<div><div>The rapid expansion of the video game market intensifies customers’ difficulty in selecting preference-aligned games. Although online reviews offer valuable insights, effectively leveraging this information remains challenging. To address this, we propose S-Kano-TOPSIS, a personalized ranking method for video games that integrates requirement categories and public opinion. First, BERTopic is used to extract customer requirements (CRs), and their performance is evaluated via sentiment analysis using a BW-CNN model. Then, SHAP is applied to quantify the influence of each CR on customer satisfaction. The Kano model is employed to adjust CR importance based on their influence patterns. Furthermore, to reflect real-world decision-making, we incorporate preference similarity by analyzing reviews of games similar to those the customer has played. Finally, TOPSIS is used to generate rankings tailored to individual needs. Experiments on 72,000 reviews from eight video games demonstrate that the proposed method surpasses baseline approaches across multiple evaluation metrics. These results suggest that S-Kano-TOPSIS offers a structured and quantifiable approach to personalized video game ranking.</div></div>","PeriodicalId":55997,"journal":{"name":"Entertainment Computing","volume":"55 ","pages":"Article 101029"},"PeriodicalIF":2.4,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145265941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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