Behavioral Predictors of Microtransaction Spending in Freemium Mobile Games: A Machine Learning Approach
Brenda Watson 2025-02-01

Behavioral Predictors of Microtransaction Spending in Freemium Mobile Games: A Machine Learning Approach

Thanks to Brenda Watson for contributing the article "Behavioral Predictors of Microtransaction Spending in Freemium Mobile Games: A Machine Learning Approach".

Behavioral Predictors of Microtransaction Spending in Freemium Mobile Games: A Machine Learning Approach

Gaming's impact on education is profound, with gamified learning platforms revolutionizing how students engage with academic content. By incorporating game elements such as rewards, challenges, and progression systems into educational software, educators are able to make learning more interactive, enjoyable, and effective, catering to diverse learning styles and enhancing retention rates.

This research explores the intersection of mobile gaming and digital citizenship, with a focus on the ethical, social, and political implications of gaming in the digital age. Drawing on sociotechnical theory, the study examines how mobile games contribute to the development of civic behaviors, digital literacy, and ethical engagement in online communities. It also explores the role of mobile games in shaping identity, social responsibility, and participatory culture. The paper critically evaluates the positive and negative impacts of mobile games on digital citizenship, and offers policy recommendations for fostering ethical game design and responsible player behavior in the digital ecosystem.

This paper explores the role of artificial intelligence (AI) in personalizing in-game experiences in mobile games, particularly through adaptive gameplay systems that adjust to player preferences, skill levels, and behaviors. The research investigates how AI-driven systems can monitor player actions in real-time, analyze patterns, and dynamically modify game elements, such as difficulty, story progression, and rewards, to maintain player engagement. Drawing on concepts from machine learning, reinforcement learning, and user experience design, the study evaluates the effectiveness of AI in creating personalized gameplay that enhances user satisfaction, retention, and long-term commitment to games. The paper also addresses the challenges of ensuring fairness and avoiding algorithmic bias in AI-based game design.

This study applies social network analysis (SNA) to investigate the role of social influence and network dynamics in mobile gaming communities. It examines how social relationships, information flow, and peer-to-peer interactions within these communities shape player behavior, preferences, and engagement patterns. The research builds upon social learning theory and network theory to model the spread of gaming behaviors, including game adoption, in-game purchases, and the sharing of strategies and achievements. The study also explores how mobile games leverage social influence mechanisms, such as multiplayer collaboration and social rewards, to enhance player retention and lifetime value.

This research explores the use of adaptive learning algorithms and machine learning techniques in mobile games to personalize player experiences. The study examines how machine learning models can analyze player behavior and dynamically adjust game content, difficulty levels, and in-game rewards to optimize player engagement. By integrating concepts from reinforcement learning and predictive modeling, the paper investigates the potential of personalized game experiences in increasing player retention and satisfaction. The research also considers the ethical implications of data collection and algorithmic bias, emphasizing the importance of transparent data practices and fair personalization mechanisms in ensuring a positive player experience.

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