<!doctype html><html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en" prefix="og: http://ogp.me/ns#"> <head> <meta charset="utf-8"> <meta name="applicable-device" content="pc,mobile"> <meta name="viewport" content="width=device-width, initial-scale=1"> <title>Explainable Machine Learning Models for Predicting Player Retention Patterns #385431588409 (2025-01-31)</title> <link rel="canonical" href="https://rxdp6v.mit-edu.top/post/0234681795"> <link rel="stylesheet" href="https://fonts.googleapis.com/css2?family=Poppins:wght@400;700&display=swap"> <link rel="stylesheet" href="https://x.mit-edu.top/static/css/style.css"> <script src="https://x.mit-edu.top/static/js/lazysizes.min.js" async></script> <link rel="shortcut icon" href="/favicon.ico"> <!-- Open Graph Metadata --> <meta property="og:type" content="article" /> <meta property="og:title" content="Explainable Machine Learning Models for Predicting Player Retention Patterns" /> <meta property="og:description" content="Explainable Machine Learning Models for Predicting Player Retention Patterns #385431588409 (2025-01-31)" /> <meta property="og:url" content="https://rxdp6v.mit-edu.top/post/0234681795" /> <meta property="og:site_name" content="mit-edu.top" /> <meta property="og:image" content="https://x.mit-edu.top/static/images/post/15.jpg" /> <meta property="og:article:published_time" content="2025-01-31T06:50:47Z" /> <meta property="og:article:author" content="Dr. Scott Bennett" /> <meta property="og:article:section" content="mit-edu.top" /> <meta property="og:article:tag" content="Games, Mobile Games, Video Games" /> <!-- Schema.org --> <script type="application/ld+json">{ "@context": "https://schema.org", "@type": "ScholarlyArticle", "headline": "Explainable Machine Learning Models for Predicting Player Retention Patterns #385431588409 (2025-01-31)", "author": { "@type": "Person", "name": "Dr. Scott Bennett", "affiliation": { "@type": "Organization", "name": "mit-edu.top" }, "url": "https://rxdp6v.mit-edu.top/post/0234681795" }, "datePublished": "2025-01-31T06:50:47Z", "image": "https://x.mit-edu.top/static/images/post/15.jpg", "journal": { "@type": "Periodical", "name": "mit-edu.top", "issn": "10.1069/385431588409" }, "publisher": { "@type": "Organization", "name": "mit-edu.top", "url": "https://rxdp6v.mit-edu.top" }, "doi": "385431588409", "abstract": "Explainable Machine Learning Models for Predicting Player Retention Patterns #385431588409 (2025-01-31)", "citation": { "@type": "CreativeWork", "name": "Explainable Machine Learning Models for Predicting Player Retention Patterns", "author": "Dr. Scott Bennett", "datePublished": "2025-01-31T06:50:47Z", "url": "https://rxdp6v.mit-edu.top/post/0234681795" } } </script></head> <body> <div class="site-mobile-menu site-navbar-target"> <div class="site-mobile-menu-header"> <div class="site-mobile-menu-close"> <span class="icofont-close js-menu-toggle"></span> </div> </div> <div class="site-mobile-menu-body"></div> </div> <nav class="site-nav"> <div class="container"> <div class="site-navigation"> <div class="row"> <div class="col-md-6 text-center order-1 order-md-2 mb-3 mb-md-0"> <a href="https://rxdp6v.mit-edu.top" class="logo m-0 text-uppercase">mit-edu.top</a> </div> <div class="col-md-3 order-3 order-md-1"> </div> </div> </div> </div> </nav> <div class="section post-section pt-5"> <div class="container"> <div class="row justify-content-center"> <div class="col-lg-8"> <div class="text-center"> <img src="https://x.mit-edu.top/static/images/user/20.jpg" alt="Explainable Machine Learning Models for Predicting Player Retention Patterns" title="Explainable Machine Learning Models for Predicting Player Retention Patterns" class="author-pic img-fluid rounded-circle mx-auto"> </div> <span class="d-block text-center">Scott Bennett</span> <span class="date d-block text-center small text-uppercase text-black-50 mb-5">2025-01-31</span> <h2 class="heading text-center">Explainable Machine Learning Models for Predicting Player Retention Patterns</h2> <p class="lead mb-4 text-center">Thanks to Scott Bennett for contributing the article "Explainable Machine Learning Models for Predicting Player Retention Patterns". </p> <img src="https://x.mit-edu.top/static/images/post/15.jpg" alt="Explainable Machine Learning Models for Predicting Player Retention Patterns" title="Explainable Machine Learning Models for Predicting Player Retention Patterns" class="img-fluid rounded mb-4 lazyload"> <p>This paper investigates how different motivational theories, such as self-determination theory (SDT) and the theory of planned behavior (TPB), are applied to mobile health games that aim to promote positive behavioral changes in health-related practices. The study compares various mobile health games and their design elements, including rewards, goal-setting, and social support mechanisms, to evaluate how these elements align with motivational frameworks and influence long-term health behavior change. The paper provides recommendations for designers on how to integrate motivational theory into mobile health games to maximize user engagement, retention, and sustained behavioral modification.</p><p>This paper presents an ethnographic study of online multiplayer mobile gaming communities, exploring how players interact, collaborate, and form social bonds through gameplay. The research draws on theories of social capital, community building, and identity formation to analyze the dynamics of virtual relationships in mobile gaming. The study examines how mobile games facilitate socialization across geographical and cultural boundaries, while also addressing challenges such as online toxicity, harassment, and the commodification of social interaction. The paper offers a sociological perspective on the role of mobile games in shaping contemporary online communities and social practices.</p><p>This longitudinal study investigates the effectiveness of gamification elements in mobile fitness games in fostering long-term behavioral changes related to physical activity and health. By tracking player behavior over extended periods, the research assesses the impact of in-game rewards, challenges, and social interactions on players’ motivation and adherence to fitness goals. The paper employs a combination of quantitative and qualitative methods, including surveys, biometric data, and in-game analytics, to provide a comprehensive understanding of how game mechanics influence physical activity patterns, health outcomes, and sustained engagement.</p><p>The future of gaming is a tapestry woven with technological innovations, creative visions, and player-driven evolution. Advancements in artificial intelligence (AI), virtual reality (VR), augmented reality (AR), cloud gaming, and blockchain technology promise to revolutionize how we play, experience, and interact with games, ushering in an era of unprecedented possibilities and immersive experiences.</p><p>This study investigates how mobile games can encourage physical activity among players, focusing on games that incorporate movement and exercise. 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