Investigating the Influence of Graphical Backgrounds in Violent Video Games on Stress Levels of Competitive Players Using Machine Learning

Abstract

Violent video games (VVGs) are widely recognized for their potential to increase stress and aggression, particularly among competitive players. This study investigates the effects of different graphical backgrounds in VVGs on the stress levels of competitive players, a topic that has not been thoroughly explored in prior research. Machine learning models are employed to analyze how various background settings influence stress responses in players. Using a dataset of competitive gamers, advanced techniques such as Gradient Boosting for feature selection, Voting and Stacking Classifiers for ensemble modeling, and a Multilayer Perceptron for capturing complex patterns are applied. Significant correlations between background graphics and stress levels are revealed, providing insights into how game design elements may impact player well-being. The results offer a new perspective on the psychological effects of VVGs and propose considerations for game developers in creating less stressful gaming environments for competitive players.