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Analyzing the Impact of Player-Induced Disruptions on Game Engagement: A Framework for Identifying Addictive Gameplay
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Player-induced disruptions
Game engagement
Addictive gameplay
Behavioral modeling
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Abstract
The increasing complexity of modern multiplayer and AI-assisted games has amplified the significance of understanding the nuanced factors that drive player engagement. Among these factors, player-induced disruptions—defined as deviations from expected gameplay patterns caused intentionally or unintentionally by players—have emerged as a critical determinant of sustained engagement and potential addictive behavior. This study presents a comprehensive framework for analyzing the impact of such disruptions on game engagement, integrating insights from behavioral science, game theory, and computational modeling. Utilizing a combination of AI-driven simulations, Monte Carlo stochastic modeling, and empirical analysis of multi-player card games such as DouDiZhu and Big2, the research systematically examines how strategic, minor, and erratic disruptions influence session duration, player interactions, and overall engagement levels. Results indicate that controlled, strategic disruptions significantly enhance engagement by fostering novelty and promoting interactive dynamics, whereas excessive or erratic deviations may lead to cognitive overload and early session termination. Moreover, AI-mediated modulation of disruptions demonstrates the capacity to optimize engagement by dynamically balancing predictability and novelty according to player skill levels. Comparative analyses with established frameworks in game refinement theory and motion-based cognitive response studies reveal that disruption intensity, timing, and player expertise collectively mediate engagement outcomes, providing quantifiable thresholds for game designers to maximize player retention without compromising cognitive load. The findings further contribute to the understanding of potentially addictive gameplay by linking measurable in-game behaviors to attention, challenge, and reward mechanisms, highlighting critical considerations for ethical game design. By synthesizing theoretical foundations with empirical evidence and simulation-based modeling, this research offers a robust, generalizable framework for assessing and optimizing engagement in complex gaming environments, advancing both the academic discourse and practical methodologies for game analytics and AI-assisted design.
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