Predicting Player Churn Through Longitudinal Behavioral Analysis in Games
Justin Brooks 2025-02-08

Predicting Player Churn Through Longitudinal Behavioral Analysis in Games

Thanks to Justin Brooks for contributing the article "Predicting Player Churn Through Longitudinal Behavioral Analysis in Games".

Predicting Player Churn Through Longitudinal Behavioral Analysis in Games

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.

This paper offers a post-structuralist analysis of narrative structures in mobile games, emphasizing how game narratives contribute to the construction of player identity and agency. It explores the intersection of game mechanics, storytelling, and player interaction, considering how mobile games as “digital texts” challenge traditional notions of authorship and narrative control. Drawing upon the works of theorists like Michel Foucault and Roland Barthes, the paper examines the decentralized nature of mobile game narratives and how they allow players to engage in a performative process of meaning-making, identity construction, and subversion of preordained narrative trajectories.

This research investigates how machine learning (ML) algorithms are used in mobile games to predict player behavior and improve game design. The study examines how game developers utilize data from players’ actions, preferences, and progress to create more personalized and engaging experiences. Drawing on predictive analytics and reinforcement learning, the paper explores how AI can optimize game content, such as dynamically adjusting difficulty levels, rewards, and narratives based on player interactions. The research also evaluates the ethical considerations surrounding data collection, privacy concerns, and algorithmic fairness in the context of player behavior prediction, offering recommendations for responsible use of AI in mobile games.

This research explores the intersection of mobile gaming and behavioral economics, focusing on how in-game purchases influence player decision-making. The study analyzes common behavioral biases, such as the “anchoring effect” and “loss aversion,” that developers exploit to encourage spending. It provides insights into how these economic principles affect the design of monetization strategies and the ethical considerations involved in manipulating player behavior.

This paper investigates the ethical implications of digital addiction in mobile games, specifically focusing on the role of game design in preventing compulsive play and overuse. The research explores how game mechanics such as reward systems, social comparison, and time-limited events may contribute to addictive behavior, particularly in vulnerable populations. Drawing on behavioral addiction theories, the study examines how developers can design games that are both engaging and ethical by avoiding exploitative practices while promoting healthy gaming habits. The paper also discusses strategies for mitigating the negative impacts of digital addiction, such as incorporating breaks, time limits, and player welfare features, to reduce the risk of game-related compulsive behavior.

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