Since 2019, novel coronavirus pneumonia has been rampant around the world, and when outbreaks occur, Meetings, Incentives, Conferences and Exhibitions (MICE) events are often affected to varying degrees. In addition, in the context of the epidemic, consumers have increasingly taken the participation of MICE in charitable activities as a measure of their social responsibility and judged MICE events as good or bad accordingly. Therefore, the impact of deep learning-based good cause marketing and the Internet on MICE events in the context of the epidemic has attracted much attention. Based on the CiteSpace analysis, this study systematically reviewed the impact system of cause-related marketing on exhibition activities and fitted the neural network model with a single-factor inter-group experiment. The results show that when the complete data set is divided into 70% training set and 30% test set, the model with the training function of Train lm and seven hidden layers performs best in all models. This shows that in the process of charity marketing, the fit between consumers and charity activities determines the attitude and willingness of consumers to participate in charity marketing.

2019年以来，新冠肺炎疫情在全球肆虐，疫情发生时，会议、奖励旅游、大会和展览（MICE）活动往往受到不同程度的影响。此外，在疫情背景下，消费者越来越多地将参加会奖旅游慈善活动作为其社会责任的衡量标准，并据此判断会奖旅游活动的好坏。因此，疫情背景下基于深度学习的公益营销和互联网对MICE活动的影响备受关注。本研究基于CiteSpace分析，系统梳理了善因营销对会展活动的影响系统，并通过单因素组间实验对神经网络模型进行拟合。结果表明，当完整数据集分为70%训练集和30%测试集时，具有Train lm训练功能和7个隐藏层的模型在所有模型中表现最好。这说明在慈善营销过程中，消费者与慈善活动的契合度决定了消费者参与慈善营销的态度和意愿。