基于餐饮业网络评论的消费者情感极性分析

Analysis of Consumer Sentiment Polarity Based on Chinese Online Review of Catering Industry

首先,根据餐饮业网络评论文本对消费者情感极性进行预测,建立了Lasso-Logistic和Lasso-PCA两个预测模型.相比之下,Lasso-PCA模型整合了更多的变量信息,对文本的情感极性具有更好的预测效果;但是LassoPCA模型对变量的解释能力较弱,尤其在解释变量维度较高的情况下,Lasso-PCA模型很难分析出解释变量对被解释变量的影响.其次,对Lasso-Logistic模型的变量选择结果进一步分析发现,特色菜、服务态度和环境以及"美中不足"之处是影响消费者情感极性的显著因素.

First, to predict consumer sentiment polarity based on Chinese online review of catering industry, this study establishes Lasso-Logistic and Lasso-PCA models. By comparison, Lasso-PCA model is more accurate by integrating more information of variables. However, Lasso-PCA model has weaker explanatory power especially in the scenario of high dimensional data. Second, using the variable selection results of Lasso-Logistic model, we find that specialties,service attitude, and the external environment, as well as ＂a fly in the ointment＂ are the significant factors affecting the consumer＇s emotional polarity directly.