Explainable Machine Learning Models for Predicting Player Retention Patterns
Katherine Foster 2025-02-01

Explainable Machine Learning Models for Predicting Player Retention Patterns

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

Explainable Machine Learning Models for Predicting Player Retention Patterns

The symphony of gaming unfolds in a crescendo of controller clicks, keyboard clacks, and the occasional victorious shout that pierces through the virtual silence, marking triumphs and milestones in the digital realm. Every input, every action taken by players contributes to the immersive experience of gaming, creating a symphony of sights, sounds, and emotions that transport them to fantastical realms and engaging adventures. Whether exploring serene landscapes, engaging in intense combat, or unraveling compelling narratives, the interactive nature of gaming fosters a deep sense of engagement and immersion, making each gaming session a memorable journey.

This meta-analysis synthesizes existing psychometric studies to assess the impact of mobile gaming on cognitive and emotional intelligence. The research systematically reviews empirical evidence regarding the effects of mobile gaming on cognitive abilities, such as memory, attention, and problem-solving, as well as emotional intelligence competencies, such as empathy, emotional regulation, and interpersonal skills. By applying meta-analytic techniques, the study provides robust insights into the cognitive and emotional benefits and drawbacks of mobile gaming, with a particular focus on game genre, duration of gameplay, and individual differences in player characteristics.

This paper examines the psychological factors that drive player motivation in mobile games, focusing on how developers can optimize game design to enhance player engagement and ensure long-term retention. The study investigates key motivational theories, such as Self-Determination Theory and the Theory of Planned Behavior, to explore how intrinsic and extrinsic factors, such as autonomy, competence, and relatedness, influence player behavior. Drawing on empirical studies and player data, the research analyzes how different game mechanics, such as rewards, achievements, and social interaction, shape players’ emotional investment and commitment to games. The paper also discusses the role of narrative, social comparison, and competition in sustaining player motivation over time.

This study applies social psychology theories to understand how group identity and collective behavior are formed and manifested within multiplayer mobile games. The research investigates the ways in which players form alliances, establish group norms, and engage in cooperative or competitive behaviors. By analyzing case studies of popular multiplayer mobile games, the paper explores the role of ingroups and outgroups, social influence, and group polarization within game environments. It also examines the psychological effects of online social interaction in gaming communities, discussing how mobile games foster both prosocial behavior and toxic interactions within groups.

This paper explores the use of artificial intelligence (AI) in predicting player behavior in mobile games. It focuses on how AI algorithms can analyze player data to forecast actions such as in-game purchases, playtime, and engagement. The research examines the potential of AI to enhance personalized gaming experiences, improve game design, and increase player retention rates.

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