Journal
HEALTHCARE
Volume 8, Issue 3, Pages -Publisher
MDPI
DOI: 10.3390/healthcare8030200
Keywords
public health emergencies; online education platform; user satisfaction prediction; emotion mining
Funding
- National Social Science Foundation of China [19ZDA122]
- Contemporary Business and Trade Research Center
- Center for Collaborative Innovation Studies of Modern Business of Zhejiang Gongshang University of China [14SMXY05YB]
- Key project of Higher education research of Zhejiang Gongshang University in 2020 (the construction path and influence promotion Mechanism of curriculum thought and politics driven by big data) [Xgz005]
- Research and Innovation Fund for Postgraduates of Zhejiang Gongshang University of China in 2020 [19020040032]
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The outbreak of Corona Virus Disease 2019 (COVID-19) in various countries at the end of last year has transferred traditional face-to-face teaching to online education platforms, which directly affects the quality of education. Taking user satisfaction on online education platforms in China as the research object, this paper uses a questionnaire survey and web crawler to collect experience data of online and offline users, constructs a customer satisfaction index system by analyzing emotion and the existing literature for quantitative analysis, and builds aback propagation (BP) neural network model to forecast user satisfaction. The conclusion shows that users' personal factors have no direct influence on user satisfaction, while platform availability has the greatest influence on user satisfaction. Finally, suggestions on improving the online education platform are given to escalate the level of online education during the COVID-19 pandemic, so as to promote the reform of information-based education.
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