摘要
【目的】通过对评论文本进行文本分析,研究影响酒店用户满意度的因素,为酒店管理者提供建议。【方法】利用Word2Vec对Tripadvisor.com酒店评论进行特征抽取和降维,结合情感分析技术,提取每类特征对应的情感,构建计量经济模型分析酒店特征评价与用户满意度的关系。【结果】研究结果表明:(1)评论文本的情感表达越积极满意度越高,但这种影响并非线性的,而是呈现"U"形的;(2)用户评论文本中提到的特征类别数越多,该用户越有可能倾向不满意;(3)消费者对豪华型酒店和经济型酒店特征类别的关注存在显著差异,消费者对前者更关注员工服务,对后者更注重清洁度;(4)对豪华型酒店,消费者满意度受到网络(Internet)这个特征维度的显著影响,而对于经济型酒店该维度的影响则不显著。【局限】样本的选择不够全面,未来可爬取多个城市数据进行更全面分析。【结论】从评论文本角度建立了酒店特征与消费者满意度的联系,为酒店在线口碑研究提供了理论依据。
[Objective] This paper analyzes the online hotel reviews to identify the factors influencing the customer＇s satisfaction, and then provides suggestion to the management. [Methods] First, we extracted features and reduced dimensionality of travelers＇ comments from Tripadvisor.com with the help of Word2Vec technique. Secondly, we extracted the characteristics of each type of the corresponding emotion based on sentiment analysis technology. Finally, we constructed an econometric model to analyze the correlation between the hotel reviews and users＇ satisfaction. [Results] We found that positive reviewers were generally satisfied with the hotel service, however, there was no linear relations between the two factors. The more feature categories mentioned by the user in comments, the more likely he or she was not satisfied. The consumers paid more attention to the staff of the luxury hotels, while cared the cleanliness of the economic ones. Consumers＇ attitudes towards luxury hotels were significantly affected by the Internet, which posed less obvious influences to the economic ones. [Limitations] The sample was not comprehensive, and more studies are needed to analyze data from multiple cities. [Conclusions] This study lays theoretical foundation for the online word-of-mouth research from the perspective of user generated contents.
作者
吴维芳
高宝俊
杨海霞
孙含琳
Wu Weifang Gao Baojun Yang Haixia Sun Hanlin(Economics and Management School, Wuhan University, Wuhan 430072, Chin)
出处
《数据分析与知识发现》
CSSCI
CSCD
2017年第3期62-71,共10页
Data Analysis and Knowledge Discovery
关键词
评论文本
酒店特征
情感分析
消费者满意度
Comment Text Hotel Features Sentiment Analysis Consumer Satisfaction
