Explainable Machine Learning Models for Predicting Player Retention Patterns
Brenda Watson 2025-02-01

Explainable Machine Learning Models for Predicting Player Retention Patterns

Thanks to Brenda Watson for contributing the article "Explainable Machine Learning Models for Predicting Player Retention Patterns".

Explainable Machine Learning Models for Predicting Player Retention Patterns

This study presents a multidimensional framework for understanding the diverse motivations that drive player engagement across different mobile game genres. By drawing on Self-Determination Theory (SDT), the research examines how intrinsic and extrinsic motivation factors—such as achievement, autonomy, social interaction, and competition—affect player behavior and satisfaction. The paper explores how various game genres (e.g., casual, role-playing, and strategy games) tailor their game mechanics to cater to different motivational drivers. It also evaluates how player motivation impacts retention, in-game purchases, and long-term player loyalty, offering a deeper understanding of game design principles and their role in shaping player experiences.

This paper examines how mobile games can enhance players’ psychological empowerment by improving their self-efficacy and confidence through gameplay. The research investigates how game mechanics such as challenges, achievements, and skill development contribute to a player's sense of mastery and competence. Drawing on psychological theories of self-efficacy and motivation, the study explores how mobile games can be designed to provide players with a sense of accomplishment and personal growth, particularly in games that focus on skill-based tasks, puzzles, and strategy. The paper also explores the impact of mobile games on players' overall well-being, particularly in terms of their confidence and ability to overcome challenges in real life.

This paper applies Cognitive Load Theory (CLT) to the design and analysis of mobile games, focusing on how game mechanics, narrative structures, and visual stimuli impact players' cognitive load during gameplay. The study investigates how high levels of cognitive load can hinder learning outcomes and gameplay performance, especially in complex puzzle or strategy games. By combining cognitive psychology and game design theory, the paper develops a framework for balancing intrinsic, extraneous, and germane cognitive load in mobile game environments. The research offers guidelines for developers to optimize user experiences by enhancing mental performance and reducing cognitive fatigue.

This study investigates the potential of blockchain technology to decentralize mobile gaming, offering new opportunities for player empowerment and developer autonomy. By leveraging smart contracts, decentralized finance (DeFi), and non-fungible tokens (NFTs), blockchain could allow players to truly own in-game assets, trade them across platforms, and participate in decentralized governance of games. The paper examines the technological challenges, economic opportunities, and legal implications of blockchain integration in mobile gaming ecosystems. It also considers the ethical concerns regarding virtual asset ownership and the potential for blockchain to disrupt existing monetization models.

This study applies neuromarketing techniques to analyze how mobile gaming companies assess and influence player preferences, focusing on cognitive and emotional responses to in-game stimuli. By using neuroimaging, eye-tracking, and biometric sensors, the research provides insights into how game mechanics such as reward systems, narrative engagement, and visual design elements affect players’ neurological responses. The paper explores the implications of these findings for mobile game developers, with a particular emphasis on optimizing player engagement, retention, and monetization strategies through the application of neuroscientific principles.

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