[目的/意义] 大数据环境下，文本挖掘和情感分析技术在产品、服务等网络点评分析中得到越来越广泛的应用。通过对大规模文本数据情感挖掘，研究影响企业舆情的关键要素。[方法/过程] 基于中国大陆292个城市103 878家酒店的2 500多万条网络点评数据，挖掘企业在线舆情，识别影响顾客服务体验的关键内容要素。采用探索性因子分析方法对关键要素进行归类，并通过多元回归分析得出评论内容要素与顾客总体满意度之间的关系。[结果/结论] 酒店客房要素和电器要素对酒店业顾客总体满意度影响最大。本研究方法和结论为服务企业营销和管理的大数据商业分析研究提供参考。

[Purpose/significance] In the era of big data, text mining and sentiment analysis technologies have been widely used in the analysis of online reviews (ORs). Through the large-scale text data mining, the key factors influencing the public opinion of enterprises are studied. [Method/process] We collected more than twenty-five million hotel online reviews from 103878 hotels, identifying key content elements that affected the customer service experience. [Result/conclusion] Through the exploratory factor analysis and the multiple regression analysis, the authors explore the relationships between the hotel customer experience and satisfaction. It is hoped that this study sets an example for the development of business analytics in enterprises marketing and management.