情报科学 ›› 2021, Vol. 39 ›› Issue (5): 53-61.

• 理论研究 • 上一篇    下一篇

基于评论数据的文本语义挖掘与情感分析

  

  • 出版日期:2021-05-01 发布日期:2021-05-11

  • Online:2021-05-01 Published:2021-05-11

摘要: 【目的/意义】基于互联网海量评论数据进行情报分析,挖掘出影响客户服务评价和满意度的关键因素,了 解客户差评背后的原因,对提升企业客户关系管理水平具有重要意义。【方法/过程】通过词云图、语义网络特征关 联分析、LDA主题模型的特征分析以及基于语义的情感词典方法,基于百度口碑中十家快递企业的客户评论数据 进行了情感计算与分析。【结果/结论】影响客户情感倾向的主要因素为:物流速度、服务态度、电话服务、投诉处理、 物流信息更新、时效性以及收费价格。基于上述结果提出了对策与建议。【创新/局限】基于现实世界真实数据,采 用数据挖掘方法分析客户情感倾向,为客户情感关键影响因素识别提供了数据科学的研究范式。

Abstract: 【Purpose/significance】Sentiment analysis based on massive internet comment data, mining the key factors that affect cus⁃ tomer service evaluation and satisfaction, and understanding the reasons behind negative reviews are of great significance to improving the level of enterprise customer relationship management.【Method/process】Through word cloud, feature association analysis of the se⁃ mantic network, the feature analysis of the LDA topic model, and the semantic-based sentiment dictionary method, we performed senti⁃ ment calculation and analysis based on the customer reviews data of ten express companies in Baidu reputation.【Result/conclusion】 The main factors affecting the emotional tendency of customers include: logistics speed, service attitude, telephone service, complaint handling, logistics information update, timeliness and charging price. Based on the above results, countermeasures and suggestions are proposed.【Innovation/limitation】Based on the real world data, the method of data mining is used to analyze customer emotion tenden⁃ cy, which provides a research paradigm of data science for the identification of key influencing factors of customer emotion.