Gender and Personality Trait Measures Impact Degree of Affect Change in a Hedonic Computing Paradigm

Abstract

To date, affective computing research has acknowledged individual differences with regard to detecting affect, yet little research has explored how these individual differences may determine the degree to which affective computing is successful in manipulating the affect of specific computer users. The current study used individual difference measures to predict how much an individual can be influenced by a hedonic computing paradigm: a simple trivia game. Female participants responded in a greater way to positive affective feedback about their performance than did men. Moreover, several personality traits, including neuroticism, narcissism, self-esteem, and extraversion, augmented the degree to which affect changed as a result of playing the game. The results are consistent with the gender differences hypothesis, and the authors conclude that individual differences, particularly gender and personality traits, play a large role in the potential impact of computing platforms and would be useful in personalizing the affective nature of the human–computer interaction.