摘要
线上餐饮平台兴起后,更多的消费者选择在网上订餐,在线评论数据量急剧增加。大量的评论数据背后隐藏着消费者对于美食的满意度因素,这些文本数据客观地反映了消费者的满意度情况,其中,回头客再次选择的因素更加值得餐饮商家关注。文章以美团网站五种餐饮类别的50000条数据为研究对象,对文本数据进行词频统计、语义网络图和系统聚类分析,认为影响回头客满意度的主要因素依次为餐品味道、菜品种类、服务态度、环境整洁及价格实惠。
The rise of online catering platforms has enabled more consumers to choose to order online,resulting in a sharp increase in online review data.The large amount of review data hides consumers’satisfaction with food.These text data objectively reflect consumers’satisfaction.Among them,the factors that make the returned customers choose again are more worthy of attention for catering businesses.This paper takes 50000 pieces of data from five catering categories on the Meituan website as the research object.Through word frequency statistics,semantic network graphs and systematic clustering analysis of text data,it is concluded that the main factors determining the satisfaction of returned customers are in the following sequence:food taste,variety of dishes,service attitude,clean environment and affordable prices.
作者
李薇
杨东山
LI Wei;YANG Dongshan(School of Economics and Management,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《重庆邮电大学学报（社会科学版）》
2021年第2期125-134,共10页
Journal of Chongqing University of Posts and Telecommunications(Social Science Edition)
基金
重庆市社会科学规划一般项目:“放纵物自律物”视角下自媒体内容产品选择行为及引导研究(2019YBGL065)。
关键词
文本挖掘
系统聚类
语义网络
可视化分析
text mining
systematic clustering
semantic network
visual analysis
