Sicheng Pan;Gary J. W. Xu;Kun Guo;Seop Hyeong Park;Hongliang Ding
Souls-like games are one of the most popular and emerging genres in the contemporary gaming world. This study compared the behavioral characteristics, perspectives, and emotional expressions of players in Souls-like games from different cultural backgrounds, specifically examining the distinctions and commonalities among them. Natural language processing techniques were employed to analyze English, Chinese, and Russian reviews of 17 Souls-like games to investigate players' gaming experiences, including gameplay behaviors, game evaluations, and emotional experiences. The findings revealed significant disparities among players from different cultures in all three aspects of their engagement with Souls-like games. Specifically, these players exhibited significant culture-related variations in their behavioral characteristics toward Souls-like games. In terms of perspectives, English-speaking players tended to focus more on game optimization, whereas Chinese and Russian players paid greater attention to game combat design. Regarding emotional expressions, Chinese players were more prone to exhibit emotions of anger and disgust, while English and Russian players displayed a more neutral emotional stance. These cultural insights provide valuable information for game developers to better meet the needs and expectations of players from different cultural backgrounds. This study not only broadens our understanding of player behaviors and cultural influences but also lends robust support to cross-cultural gaming research.
{"title":"Cultural Insights in Souls-Like Games: Analyzing Player Behaviors, Perspectives, and Emotions Across a Multicultural Context","authors":"Sicheng Pan;Gary J. W. Xu;Kun Guo;Seop Hyeong Park;Hongliang Ding","doi":"10.1109/TG.2024.3366239","DOIUrl":"10.1109/TG.2024.3366239","url":null,"abstract":"<italic>Souls-like</i>\u0000 games are one of the most popular and emerging genres in the contemporary gaming world. This study compared the behavioral characteristics, perspectives, and emotional expressions of players in \u0000<italic>Souls-like</i>\u0000 games from different cultural backgrounds, specifically examining the distinctions and commonalities among them. Natural language processing techniques were employed to analyze English, Chinese, and Russian reviews of 17 \u0000<italic>Souls-like</i>\u0000 games to investigate players' gaming experiences, including gameplay behaviors, game evaluations, and emotional experiences. The findings revealed significant disparities among players from different cultures in all three aspects of their engagement with \u0000<italic>Souls-like</i>\u0000 games. Specifically, these players exhibited significant culture-related variations in their behavioral characteristics toward \u0000<italic>Souls-like</i>\u0000 games. In terms of perspectives, English-speaking players tended to focus more on game optimization, whereas Chinese and Russian players paid greater attention to game combat design. Regarding emotional expressions, Chinese players were more prone to exhibit emotions of anger and disgust, while English and Russian players displayed a more neutral emotional stance. These cultural insights provide valuable information for game developers to better meet the needs and expectations of players from different cultural backgrounds. This study not only broadens our understanding of player behaviors and cultural influences but also lends robust support to cross-cultural gaming research.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 4","pages":"758-769"},"PeriodicalIF":1.7,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simone Bassanelli, Antonio Bucchiarone, Federica Gini
{"title":"GamiDOC: The Importance of Designing Gamification in a Proper Way","authors":"Simone Bassanelli, Antonio Bucchiarone, Federica Gini","doi":"10.1109/tg.2024.3364061","DOIUrl":"https://doi.org/10.1109/tg.2024.3364061","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"745 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Examining the Usability of the Moirai Serious Game Authoring Platform","authors":"Andrei Torres, Bill Kapralos, Adam Dubrowski","doi":"10.1109/tg.2024.3360918","DOIUrl":"https://doi.org/10.1109/tg.2024.3360918","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"30 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While reinforcement learning (RL) is gaining popularity in gameplay, creating a generalized RL model is still challenging. This study presents BaziGooshi , a generalized RL solution for games, focusing on two different types of games: 1) a puzzle game Candy Crush Friends Saga and 2) a platform game Sonic the Hedgehog Genesis . BaziGooshi rewards RL agents for mastering a set of intrinsic basic skills as well as achieving the game objectives. The solution includes a hybrid model that takes advantage of a combination of several agents pretrained using intrinsic or extrinsic rewards to determine the actions. We propose an RL-based method for assigning weights to the pretrained agents. Through experiments, we show that the RL-based approach improves generalization to unseen levels, and BaziGooshi surpasses the performance of most of the defined baselines in both games. Also, we perform additional experiments to investigate further the impacts of using intrinsic rewards and the effects of using different combinations in the proposed hybrid models.
{"title":"BaziGooshi: A Hybrid Model of Reinforcement Learning for Generalization in Gameplay","authors":"Sara Karimi;Sahar Asadi;Amir H. Payberah","doi":"10.1109/TG.2024.3355172","DOIUrl":"10.1109/TG.2024.3355172","url":null,"abstract":"While reinforcement learning (RL) is gaining popularity in gameplay, creating a generalized RL model is still challenging. This study presents \u0000<sc>BaziGooshi</small>\u0000, a generalized RL solution for games, focusing on two different types of games: 1) a puzzle game \u0000<italic>Candy Crush Friends Saga</i>\u0000 and 2) a platform game \u0000<italic>Sonic the Hedgehog Genesis</i>\u0000. \u0000<sc>BaziGooshi</small>\u0000 rewards RL agents for mastering a set of intrinsic basic skills as well as achieving the game objectives. The solution includes a hybrid model that takes advantage of a combination of several agents pretrained using intrinsic or extrinsic rewards to determine the actions. We propose an RL-based method for assigning weights to the pretrained agents. Through experiments, we show that the RL-based approach improves generalization to unseen levels, and \u0000<sc>BaziGooshi</small>\u0000 surpasses the performance of most of the defined baselines in both games. Also, we perform additional experiments to investigate further the impacts of using intrinsic rewards and the effects of using different combinations in the proposed hybrid models.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"722-734"},"PeriodicalIF":1.7,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mechanics are one of the pillars of gameplay, enabled by the underlying implementation of the game and subject to constant changes during development. In particular, self-amending mechanics adjust themselves dynamically and are a common source of coupled code. The Rulebook is an architectural pattern that generalizes how developers prevent coupled code in self-amending mechanics, based on a careful research process including a systematic literature review, semistructured interviews with professional developers, and quasi-experiments. The pattern codifies changes to the game state as “effect” objects, which it matches against a dynamic pool of rules. Each rule may amend, resolve, or chain effects. By preventing the control flow of the game from becoming coupled to the specific interactions of mechanics while also promoting an extensible and flexible structure for self-amendment, our solution reduces the time developers need to iterate on the design of mechanics. This article details the Rulebook pattern and presents a case study demonstrating its design process in three different implementations of open-source jam games. Together with the typification of self-amending mechanics, this article formalizes a novel, state-of-the-art toolset for architecting games.
{"title":"Rulebook: An Architectural Pattern for Self-Amending Mechanics in Digital Games","authors":"Wilson Kazuo Mizutani;Fabio Kon","doi":"10.1109/TG.2024.3359439","DOIUrl":"10.1109/TG.2024.3359439","url":null,"abstract":"Mechanics are one of the pillars of gameplay, enabled by the underlying implementation of the game and subject to constant changes during development. In particular, self-amending mechanics adjust themselves dynamically and are a common source of coupled code. The \u0000<italic>Rulebook</i>\u0000 is an architectural pattern that generalizes how developers prevent coupled code in self-amending mechanics, based on a careful research process including a systematic literature review, semistructured interviews with professional developers, and quasi-experiments. The pattern codifies changes to the game state as “effect” objects, which it matches against a dynamic pool of rules. Each rule may amend, resolve, or chain effects. By preventing the control flow of the game from becoming coupled to the specific interactions of mechanics while also promoting an extensible and flexible structure for self-amendment, our solution reduces the time developers need to iterate on the design of mechanics. This article details the \u0000<italic>Rulebook</i>\u0000 pattern and presents a case study demonstrating its design process in three different implementations of open-source jam games. Together with the typification of self-amending mechanics, this article formalizes a novel, state-of-the-art toolset for architecting games.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"711-721"},"PeriodicalIF":1.7,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Countdown VR: a Serious Game in Virtual Reality to Develop Mental Computation Skills","authors":"Hubert Cecotti, Mathilde Leray, Michael Callaghan","doi":"10.1109/tg.2024.3357452","DOIUrl":"https://doi.org/10.1109/tg.2024.3357452","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"174 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Systematic Review of Model-Driven Game Development Studies","authors":"Amirreza Payandeh, Mohammadreza Sharbaf, Shekoufeh Kolahdouz Rahimi","doi":"10.1109/tg.2024.3356408","DOIUrl":"https://doi.org/10.1109/tg.2024.3356408","url":null,"abstract":"","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"10 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Reza Taesiri;Finlay Macklon;Sarra Habchi;Cor-Paul Bezemer
Gameplay videos offer valuable insights into player interactions and game responses, particularly data about game bugs. Despite the abundance of gameplay videos online, extracting useful information remains a challenge. This article introduces a method for searching and extracting relevant videos from extensive video repositories using English text queries. Our approach requires no external information, like video metadata; it solely depends on video content. Leveraging the zero-shot transfer capabilities of the contrastive language–image pretraining model, our approach does not require any data labeling or training. To evaluate our approach, we present the GamePhysics dataset, comprising 26 954 videos from 1873 games that were collected from the GamePhysics section on the Reddit website. Our approach shows promising results in our extensive analysis of simple and compound queries, indicating that our method is useful for detecting objects and events in gameplay videos. Moreover, we assess the effectiveness of our method by analyzing a carefully annotated dataset of 220 gameplay videos. The results of our study demonstrate the potential of our approach for applications, such as the creation of a video search tool tailored to identifying video game bugs, which could greatly benefit quality assurance teams in finding and reproducing bugs.
{"title":"Searching Bug Instances in Gameplay Video Repositories","authors":"Mohammad Reza Taesiri;Finlay Macklon;Sarra Habchi;Cor-Paul Bezemer","doi":"10.1109/TG.2024.3355285","DOIUrl":"10.1109/TG.2024.3355285","url":null,"abstract":"Gameplay videos offer valuable insights into player interactions and game responses, particularly data about game bugs. Despite the abundance of gameplay videos online, extracting useful information remains a challenge. This article introduces a method for searching and extracting relevant videos from extensive video repositories using English text queries. Our approach requires no external information, like video metadata; it solely depends on video content. Leveraging the zero-shot transfer capabilities of the contrastive language–image pretraining model, our approach does not require any data labeling or training. To evaluate our approach, we present the \u0000<monospace>GamePhysics</monospace>\u0000 dataset, comprising 26 954 videos from 1873 games that were collected from the \u0000<uri>GamePhysics</uri>\u0000 section on the Reddit website. Our approach shows promising results in our extensive analysis of simple and compound queries, indicating that our method is useful for detecting objects and events in gameplay videos. Moreover, we assess the effectiveness of our method by analyzing a carefully annotated dataset of 220 gameplay videos. The results of our study demonstrate the potential of our approach for applications, such as the creation of a video search tool tailored to identifying video game bugs, which could greatly benefit quality assurance teams in finding and reproducing bugs.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"697-710"},"PeriodicalIF":1.7,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel L. Gardner;LouAnne Boyd;Reginald T. Gardner
Digital games are a multi-billion-dollar industry whose production and consumption extend globally. Representation in games is an increasingly important topic. As those who create and consume the medium grow ever more diverse, it is essential that player or user-experience research, usability, and any consideration of how people interface with their technology are exercised through inclusive and intersectional lenses. Previous research has identified how character configuration interfaces preface white-male defaults (Gardner and Tanenbaum 2018), (Gardner and Tanenbaum 2021), and (Mastro and Behm-Morawitz 2005). This study relies on 1-on-1 play interviews where diverse participants attempt to create “themselves” in a series of games and on group design activities to explore how participants may envision more inclusive character configuration interface design. Our interview findings describe specific points of tension in the process of creating characters in existing interfaces and the sketches participants–collaborators produced to challenge the homogeneity of current interface designs. This project amplifies the perspective of diverse participants–collaborators to provide constructive implications and a series of principles for designing more inclusive character configuration interfaces, which support more diverse stories and gameworlds by reconfiguring the constraints that shape those stories and gameworlds.
数字游戏是一个价值数十亿美元的产业，其生产和消费遍及全球。游戏中的代表性是一个日益重要的话题。随着创造和消费游戏媒介的人越来越多样化，玩家或用户体验研究、可用性以及对人们如何与他们的技术进行交互的任何考虑，都必须通过包容性和交叉性的视角来进行。之前的研究已经确定了角色配置界面是如何预设白人-男性默认设置的（Gardner and Tanenbaum 2018）、（Gardner and Tanenbaum 2021）和（Mastro and Behm-Morawitz 2005）。本研究通过一对一游戏访谈，让不同参与者尝试在一系列游戏中创造 "自己"，并通过小组设计活动，探讨参与者如何设想更具包容性的角色配置界面设计。我们的访谈结果描述了在现有界面中创建角色过程中的具体紧张点，以及参与者--合作者为挑战当前界面设计的单一性而绘制的草图。本项目放大了不同参与者--合作者的观点，为设计更具包容性的角色配置界面提供了建设性的意义和一系列原则，通过重新配置塑造故事和游戏世界的约束条件，支持更多样化的故事和游戏世界。
{"title":"Piecing Together Performance: Collaborative, Participatory Research-Through-Design for Better Diversity in Games","authors":"Daniel L. Gardner;LouAnne Boyd;Reginald T. Gardner","doi":"10.1109/TG.2023.3349369","DOIUrl":"10.1109/TG.2023.3349369","url":null,"abstract":"Digital games are a multi-billion-dollar industry whose production and consumption extend globally. Representation in games is an increasingly important topic. As those who create and consume the medium grow ever more diverse, it is essential that player or user-experience research, usability, and any consideration of how people interface with their technology are exercised through inclusive and intersectional lenses. Previous research has identified how character configuration interfaces preface white-male defaults (Gardner and Tanenbaum 2018), (Gardner and Tanenbaum 2021), and (Mastro and Behm-Morawitz 2005). This study relies on 1-on-1 play interviews where diverse participants attempt to create “themselves” in a series of games and on group design activities to explore how participants may envision more inclusive character configuration interface design. Our interview findings describe specific points of tension in the process of creating characters in existing interfaces and the sketches participants–collaborators produced to challenge the homogeneity of current interface designs. This project amplifies the perspective of diverse participants–collaborators to provide constructive implications and a series of \u0000<italic>principles</i>\u0000 for designing more inclusive character configuration interfaces, which support more diverse stories and gameworlds by reconfiguring the constraints that shape those stories and gameworlds.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 3","pages":"683-696"},"PeriodicalIF":1.7,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139953765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sicheng Pan;Gary J. W. Xu;Kun Guo;Seop Hyeong Park;Hongliang Ding
In this article, we propose a nonintrusive and nonrestrictive multimodal deep learning model for estimating the engagement levels of game streamers. We incorporate three modalities from the streamers' videos (facial, pixel, and audio information) to train the multimodal neural network. Additionally, we introduce a novel interpretation technique that directly calculates the contribution of each modality to the model's classification performance without the need to retrain single-modality models. Experimental results demonstrate that our model achieves an accuracy of 77.2% on the test set, with the sound modality identified as a key modality for engagement estimation. By utilizing the proposed interpretation technique, we further analyze the modality contributions of the model in handling different categories and samples from various players. This enhances the model's interpretability and reveals its limitations, as well as future directions for improvement. The proposed approach and findings have potential applications in the fields of game streaming and audience analysis, as well as in domains related to multimodal learning and affective computing.
{"title":"Video-Based Engagement Estimation of Game Streamers: An Interpretable Multimodal Neural Network Approach","authors":"Sicheng Pan;Gary J. W. Xu;Kun Guo;Seop Hyeong Park;Hongliang Ding","doi":"10.1109/TG.2023.3348230","DOIUrl":"10.1109/TG.2023.3348230","url":null,"abstract":"In this article, we propose a nonintrusive and nonrestrictive multimodal deep learning model for estimating the engagement levels of game streamers. We incorporate three modalities from the streamers' videos (facial, pixel, and audio information) to train the multimodal neural network. Additionally, we introduce a novel interpretation technique that directly calculates the contribution of each modality to the model's classification performance without the need to retrain single-modality models. Experimental results demonstrate that our model achieves an accuracy of 77.2% on the test set, with the sound modality identified as a key modality for engagement estimation. By utilizing the proposed interpretation technique, we further analyze the modality contributions of the model in handling different categories and samples from various players. This enhances the model's interpretability and reveals its limitations, as well as future directions for improvement. The proposed approach and findings have potential applications in the fields of game streaming and audience analysis, as well as in domains related to multimodal learning and affective computing.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 4","pages":"746-757"},"PeriodicalIF":1.7,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142218211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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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