摘要
为了提出大数据时代的消费者满意度动态监测方法,帮助企业实时了解消费者满意度动态及影响因素,从京东抓取乳制品评论数据,基于双因素理论和文本挖掘方法进行消费者满意度监测,并分析其影响因素.建立了激励因素和保健因素词库,构建了消费者满意度动态监测模型并绘制动态监测图,分析了满意度波动的原因.乳制品评论数据的实证表明,该模型能够有效监测消费者满意度,并分析波动的影响因素.
To propose a dynamic monitoring method for consumer satisfaction in the period of big data to help companies keep up with consumer satisfaction and its influencing factors.The comment data of dairy products was captured from Jingdong Mall,the monitoring model was conducted based on the two-factor theory and text mining methods,and the factors affecting the fluctuation of satisfaction were analyzed by statistics.The motivators and hygiene factors and related words were extracted,and a dynamic monitoring model of consumer satisfaction was constructed and a dynamic monitoring chart was drawn.Reasons for fluctuations in satisfaction were analyzed.The empirical analysis of dairy product comment shows that this model can monitor consumer satisfaction effectively and analyze the reasons for fluctuations in satisfaction.
作者
金慧峰
王积建
宦梅丽
陈鹏飞
侯云先
JIN Hui-feng;WANG Ji-jian;HUAN Mei-li;CHEN Peng-fei;HOU Yun-xian(Zhejiang Industry&Trade Vocational College College of Information and Communication,Wenzhou 325003,China;Zhejiang Industry&Trgide Vocational College Department of Humanities,Wenzhou 325003,China;China Agricultural University College of Economics and Management,Beijing 100083,China)
出处
《数学的实践与认识》
北大核心
2020年第14期274-287,共14页
Mathematics in Practice and Theory
基金
浙江省高校“十三五”优势专业建设项目(浙教高校[2016]164号)
浙江省教育厅高等教育“十三五”第一批教学改革研究项目:高等数学CDIO-MEM教育模式改革的研究与实践(jg20180747)。
关键词
消费者满意度
动态监测
双因素理论
文本挖掘
在线评价
consumer satisfaction
dynamic monitoring
two-factor theory
text mining
on-line evaluation
