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数字技术环境下博物馆参观者情绪的测量与特征研究

Research on the measurement and characteristics of museum visitors' emotions under digital technology environment.

作者信息

Zhang Ting, Qi Zipeng, Guan Weiwei, Zhang Cheng, Jin Dingli

机构信息

Economics and Management School, Wuhan University, Wuhan, Hubei, China.

Ningbo National Institute Insurance Development (NIID), Wuhan University, Ningbo, China.

出版信息

Front Hum Neurosci. 2023 Sep 4;17:1251241. doi: 10.3389/fnhum.2023.1251241. eCollection 2023.

Abstract

What kind of emotional experience does the application of digital technology in museums create for museum visitors? Can it be measured accurately and in real-time? What are its characteristics? This paper utilizes EEG signals and the PAD emotional model as research methods to conduct real-time digital measurement of visitors' emotional experiences at Tianyi Pavilion Museum in Ningbo City, focusing on their physiological and psychological reactions.The results show that: (1) In a quasi-experimental environment, linear SVM, polynomial kernel SVM, and Gaussian kernel SVM can all accurately classify the emotional tendencies of museum visitors with success rate of over 72%. (2) In a quasi-experimental environment, it is feasible and reliable to measure the immediate digital emotional experiences of visitors using EEG signals and the PAD emotion model. Based on this, we can summarize the characteristics of emotional tendencies among different demographic groups of museum visitors.

摘要

数字技术在博物馆中的应用为博物馆参观者带来了怎样的情感体验?能否进行准确的实时测量?其特点是什么?本文采用脑电信号和PAD情感模型作为研究方法,对宁波市天一阁博物馆参观者的情感体验进行实时数字测量,重点关注他们的生理和心理反应。结果表明:(1)在准实验环境中,线性支持向量机、多项式核支持向量机和高斯核支持向量机都能准确分类博物馆参观者的情感倾向,成功率超过72%。(2)在准实验环境中,利用脑电信号和PAD情感模型测量参观者即时的数字情感体验是可行且可靠的。基于此,我们可以总结出博物馆参观者不同人口统计学群体情感倾向的特点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e164/10507405/62c09d9e8882/fnhum-17-1251241-g001.jpg

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