摘要
爬取新浪微博中国移动官方账号评论区的1560条投诉文本作为普通投诉数据,以及黑猫投诉平台对中国移动的4600条投诉文本作为升级投诉数据,对数据进行预处理。采用word2vec技术,将预处理后的投诉文本数据转化为数值数据,通过计算向量余弦相似度,获取容易上升为升级投诉的普通投诉数据,即潜在升级投诉数据,并对其主题进行总结。通过对升级投诉文本进行LDA主题分析,获取升级投诉的主题,从而分析客户进行升级投诉的原因,为运营商准确挖掘潜在升级投诉客户提供新思路,对运营商的客户投诉管理提出切实可行的建议。
Through data crawling,1560 complaint texts in the comment area of China Mobile’s official microblog in sina are taken as ordinary complaint data and 4600 complaint texts about China Mobile from the black cat complaint platform are taken as further complaint data,and then the data is preprocessed.Word2vec technology is used to convert the preprocessed complaint text data into numerical data,and by calculating the vector cosine similarity,the ordinary complaints that are easy to become further complaints are obtained,and the themes are summarized.The LDA(linear discriminant analysis)subject analysis is used to obtain the subjects of the further complaints,so as to analyze their reasons.This study aims to provide new ideas for operators to accurately locate potential customers with further complaints,and put forward suggestions for operators’customer complaint management.
作者
张爱华
于涵
陈超雨
ZHANG Aihua;YU Han;CHEN Chaoyu(School of Economics and Management,Beijing University of Posts and Telecommunications,Beijing 100876,China)
出处
《北京邮电大学学报（社会科学版）》
2022年第5期32-38,57,共8页
Journal of Beijing University of Posts and Telecommunications(Social Sciences Edition)
基金
通鼎研究基金。
关键词
升级投诉
客户挖掘
文本分析
further complaints
customer mining
text analysis
