AUTHOR=Ding Yi , Guo Ran , Lyu Wei , Zhang Wengang 

TITLE=Gender effect in human–machine communication: a neurophysiological study

JOURNAL=Frontiers in Human Neuroscience

VOLUME=Volume 18 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2024.1376221

DOI=10.3389/fnhum.2024.1376221

ISSN=1662-5161

ABSTRACT=Purpose -This study aims to investigate the neural mechanism of how virtual chatbots' gender might influence user usage intention and gender differences in human-machine communication.Approach -Event-related potentials (ERPs) and subjective questionnaire methods were used to explore the usage intention of virtual chatbots, and statistical analysis was conducted through repeated measures ANOVA.Results/Findings -The results of ERPs revealed that female virtual chatbots, compared to male virtual chatbots, evoked a larger amplitude of P100, P200, implying a greater allocation of attentional resources towards female-virtual chatbots. Taking into account participant gender, the gender factors of virtual chatbots continued influencing N100, P100, and P200. Specifically, among female participants, female virtual chatbots induced a larger P100, P200 than male ones, indicating that female participants exhibited more attentional resources and positive emotions towards the same-partner gender. Conversely, among male participants, male virtual chatbots induced a larger N100 than female ones, suggesting that male participants allocated to more attentional resources toward male virtual chatbots. The results of the subjective questionnaire showed that regardless of participants gender, users have a larger usage intention toward female virtual chatbots than male ones. Value -Our findings can provide designers with neurophysiological insights to better design virtual chatbots that cater to users' psychological needs.