基于评论数据的文本语义挖掘与情感分析  

Sentiment Analysis and Text Data Mining Based on Reviewing Data

作　　者：张公让[1] 鲍超 王晓玉[2] 顾东晓[1,3] 杨雪洁[1] 李康 ZHANG Gong-rang;BAO Chao;WANGXiao-yu;GU Dong-xiao;YANG Xue-jie;LI Kang(School of management,Hefei University of Technology,Hefei 230009,China;Anhui University of Chinese Medicine,Hefei 230001,China;Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education,Hefei 230009,China)

机构地区：[1]合肥工业大学管理学院,安徽合肥230009 [2]安徽中医药大学第一附属医院,安徽合肥230001 [3]过程优化与智能决策教育部重点实验室,安徽合肥230009

出　　处：《情报科学》2021年第5期53-61,共9页Information Science

基　　金：国家自然科学基金项目“基于健康大数据的老年慢性病知识组织与服务机制研究”(71771077);安徽省科技创新战略与软科学研究专项“国内外重大新兴技术发展趋势与安徽新兴产业政策研究”(201806a02020040);中央高校基本科研业务费专项资金资助“多模态智能驱动的健康大数据知识深度聚合与服务平台关键技术研究”(PA2020GDKC0020)。

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。【Purpose/significance】Sentiment analysis based on massive internet comment data, mining the key factors that affect customer 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 semantic network, the feature analysis of the LDA topic model, and the semantic-based sentiment dictionary method, we performed sentiment 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 tendency, which provides a research paradigm of data science for the identification of key influencing factors of customer emotion.

关 键 词：文本挖掘 情感分析 评论数据 语义网络 数据管理 

分 类 号：G254[文化科学—图书馆学]