Gender effect in human–machine communication: a neurophysiological study

Abstract

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PurposeThis study aimed to investigate the neural mechanism by which virtual chatbots' gender might influence users' usage intention and gender differences in human–machine communication.ApproachEvent-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/findingsThe findings of ERPs revealed that female virtual chatbots, compared to male virtual chatbots, evoked a larger amplitude of P100 and P200, implying a greater allocation of attentional resources toward female virtual chatbots. Considering participants' gender, the gender factors of virtual chatbots continued to influence N100, P100, and P200. Specifically, among female participants, female virtual chatbots induced a larger P100 and P200 amplitude than male virtual chatbots, indicating that female participants exhibited more attentional resources and positive emotions toward same-gender chatbots. Conversely, among male participants, male virtual chatbots induced a larger N100 amplitude than female virtual chatbots, indicating that male participants allocated 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 virtual chatbots.ValueOur findings could provide designers with neurophysiological insights into designing better virtual chatbots that cater to users' psychological needs.

Keywords

• virtual chatbots
• gender difference
• usage intention
• ERPs
• human–robot interaction