How neuroticism and locus of control affect user performance in high-dimensional data visualization

Abstract

The impact of individual differences, such as personality traits, on user performance and human behaviors has been studied in several fields of human–computer interaction, with a growing interest in information visualization. Although most visualizations are still designed with a universal approach, great strides have been made toward the development of user-adaptive visualizations catered to the user’s personality. We analyze how personality affects user interaction with high-dimensional visualizations. Specifically, we explore the impact of neuroticism (including its facets) and locus of control in user performance and confidence. Results suggest that neurotic individuals are faster with the scatterplot matrix, while individuals with an internal locus are more confident when using the parallel coordinates plot. In addition, results indicate that the facets of neuroticism have significant – and distinct from neuroticism – impact on user performance and confidence, pointing toward the need to analyze traits, such as neuroticism, at a lower level.