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<span class="d-block text-center">John Smith</span>
<span class="date d-block text-center small text-uppercase text-black-50 mb-5">2025-02-05</span>
<h2 class="heading text-center">Predictive Modeling of Player Drop-Off Using Ensemble Machine Learning Techniques</h2>
<p class="lead mb-4 text-center">Thanks to John Smith for contributing the article "Predictive Modeling of Player Drop-Off Using Ensemble Machine Learning Techniques".
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<p>This study explores the role of player customization in mobile games, focusing on how avatar and character customization can influence player identity, self-expression, and engagement. The research examines how customizing characters, outfits, and other in-game features enables players to create personalized experiences that reflect their preferences and identities. Drawing on social identity theory and self-concept research, the paper investigates how customization fosters emotional attachment to the game, as well as its impact on player behavior, such as social interaction and competition. The study also explores the commercial implications of offering customizable in-game items, including microtransactions and virtual economies.</p>
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<p>This study examines the ethical implications of data collection practices in mobile games, focusing on how player data is used to personalize experiences, target advertisements, and influence in-game purchases. The research investigates the risks associated with data privacy violations, surveillance, and the exploitation of vulnerable players, particularly minors and those with addictive tendencies. By drawing on ethical frameworks from information technology ethics, the paper discusses the ethical responsibilities of game developers in balancing data-driven business models with player privacy. It also proposes guidelines for designing mobile games that prioritize user consent, transparency, and data protection.</p>
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