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Gender effect in human-machine communication: a neurophysiological study.

Yi Ding¹, Ran Guo¹, Wei Lyu¹

¹School of Economics and Management, Anhui Polytechnic University, Wuhu, China.

Frontiers in Human Neuroscience

|July 26, 2024

Summary

This summary is machine-generated.

Virtual chatbot gender influences user attention and intention. Female chatbots attract more attention from female users, while male chatbots engage male users, with all users preferring female chatbots.

Keywords:

ERPs gender difference human–robot interaction usage intention virtual chatbots

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Area of Science:

Human-Computer Interaction
Neuroscience
Cognitive Psychology

Background:

Virtual chatbots are increasingly used in various applications.
Understanding user interaction with virtual agents is crucial for effective design.
The influence of virtual agent characteristics, such as gender, on user perception and behavior requires investigation.

Purpose of the Study:

To investigate the neural mechanisms underlying the influence of virtual chatbot gender on user intention.
To explore gender differences in human-machine communication with virtual chatbots.
To provide neurophysiological insights for designing more engaging virtual chatbots.

Main Methods:

Event-related potentials (ERPs) were recorded to measure neural responses.
Subjective questionnaires assessed user usage intention.
Repeated measures ANOVA was employed for statistical analysis.

Main Results:

Female virtual chatbots elicited larger P100 and P200 amplitudes, indicating greater attentional allocation.
Participant gender modulated neural responses (N100, P100, P200) to chatbot gender.
Female participants showed greater attention and positive emotion towards same-gender chatbots; male participants showed greater attention towards same-gender chatbots.
Subjective data revealed a higher usage intention towards female virtual chatbots, irrespective of participant gender.

Conclusions:

Chatbot gender significantly impacts user attentional resources and usage intention.
User and chatbot gender interact to influence neural processing and emotional responses.
Findings offer valuable neurophysiological data for designing user-centered virtual chatbots.