News - Player Typology Modeling Based on Longitudinal Gameplay Data #124746129642 (2025-02-13)

Player Typology Modeling Based on Longitudinal Gameplay Data

Thanks to Stephen Hamilton for contributing the article "Player Typology Modeling Based on Longitudinal Gameplay Data".

This paper provides a comparative legal analysis of intellectual property (IP) rights as they pertain to mobile game development, focusing on the protection of game code, design elements, and in-game assets across different jurisdictions. The study examines the legal challenges that developers face when navigating copyright, trademark, and patent law in the global mobile gaming market. By comparing IP regulations in the United States, the European Union, and Asia, the paper identifies key legal barriers and proposes policy recommendations to foster innovation while protecting the intellectual property of creators. The study also considers emerging issues such as the ownership of user-generated content and the legal status of in-game assets like NFTs.

This paper explores the use of mobile games as educational tools, assessing their effectiveness in teaching various subjects and skills. It discusses the advantages and limitations of game-based learning in mobile contexts.

This research investigates how mobile games contribute to the transhumanist imagination by exploring themes of human enhancement and augmented reality (AR). The study examines how mobile AR games, such as Pokémon Go, offer new forms of interaction between players and their physical environments, effectively blurring the boundaries between the digital and physical worlds. Drawing on transhumanist philosophy and media theory, the paper explores the implications of AR technology for redefining human perception, cognition, and embodiment. It also addresses ethical concerns related to the over-reliance on AR technologies and the potential for social disconnection.

This paper explores the application of artificial intelligence (AI) and machine learning algorithms in predicting player behavior and personalizing mobile game experiences. The research investigates how AI techniques such as collaborative filtering, reinforcement learning, and predictive analytics can be used to adapt game difficulty, narrative progression, and in-game rewards based on individual player preferences and past behavior. By drawing on concepts from behavioral science and AI, the study evaluates the effectiveness of AI-powered personalization in enhancing player engagement, retention, and monetization. The paper also considers the ethical challenges of AI-driven personalization, including the potential for manipulation and algorithmic bias.

Gaming addiction is a complex issue that warrants attention and understanding, as some individuals struggle to find a healthy balance between their gaming pursuits and other responsibilities. It's important to promote responsible gaming habits, encourage breaks, and offer support to those who may be experiencing challenges in managing their gaming habits and overall well-being.

2025-02-13

Mobile Games as a Tool for Behavioral Research: Opportunities and Challenges

This paper investigates the impact of user-centric design principles in mobile games, focusing on how personalization and customization options influence player satisfaction and engagement. The research analyzes how mobile games employ features such as personalized avatars, dynamic content, and adaptive difficulty settings to cater to individual player preferences. By applying frameworks from human-computer interaction (HCI), motivation theory, and user experience (UX) design, the study explores how these design elements contribute to increased player retention, emotional attachment, and long-term engagement. The paper also considers the challenges of balancing personalization with accessibility, ensuring that customization does not exclude or frustrate diverse player groups.

Emily Carter 2025-02-13 published post

2025-02-13

Exploring Gendered Play Patterns in Competitive Mobile Games

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.

Thomas Clark 2025-02-13 published post

2025-02-13

Predicting Player Churn Through Longitudinal Behavioral Analysis in Games

This paper offers a historical and theoretical analysis of the evolution of mobile game design, focusing on the technological advancements that have shaped gameplay mechanics, user interfaces, and game narratives over time. The research traces the development of mobile gaming from its inception to the present day, considering key milestones such as the advent of touchscreen interfaces, the rise of augmented reality (AR), and the integration of artificial intelligence (AI) in mobile games. Drawing on media studies and technology adoption theory, the paper examines how changing technological landscapes have influenced player expectations, industry trends, and game design practices.

Rebecca Cook 2025-02-13 published post

Player Typology Modeling Based on Longitudinal Gameplay Data

Related

Mobile Games as a Tool for Behavioral Research: Opportunities and Challenges

Exploring Gendered Play Patterns in Competitive Mobile Games

Predicting Player Churn Through Longitudinal Behavioral Analysis in Games

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