Akademik Veri Yönetim Sistemi
Creating A Human-Focused Future, Serra Çelik,Sevinç Gülseçen,Meltem Eryılmaz, Editör, Istanbul University Press, İstanbul, ss.158-171, 2025
This research proposes an integrated, data-driven approach to enhancing user experience in video games by combining real-time analytics, eye-tracking, facial expression recognition, and process mining. Traditional evaluation methods—such as surveys, interviews, and basic gameplay statistics—often fail to capture the immediacy and nuance of player emotions, resulting in incomplete or biased insights. To address these limitations, the proposed system collects and analyzes synchronized data from both in-game events and players’ real-time emotional states. Eye tracking data captures user attention and cognitive load, while facial recognition, supported by convolutional neural networks (CNN) trained on public datasets such as FER-2013 and AffectNet, enables the classification of emotional responses during gameplay. Simultaneously, process mining techniques are applied to event logs to uncover behavioral patterns, gameplay bottlenecks, and user flow disruptions. This multi-modal framework not only allows for deeper understanding of player behavior and emotional engagement but also offers a scalable and developer friendly solution compatible with major game engines such as Unity, Unreal Engine, and Godot. Ultimately, the system aims to support the creation of adaptive, personalized, and immersive gaming experiences—aligning player expectations with game design in real time.