摘要
社交网络平台的迅速发展,促使网络舆情成为企业获取商业情报、扩大竞争优势的重要信息来源。本文针对网络舆情环境下的企业客户关系管理问题展开研究。通过构建企业客户推动式信息反馈模型,描述了企业客户、网络用户与企业网络舆情间的联系,并依据信息反馈模型,提出变尺度聚类算法。该算法将传统聚类方法的求解过程由单一尺度分析扩展到多尺度分析,克服了实际数据聚类应用过程中的聚类结果特征不显著问题。本文选取新浪微博作为数据源,利用企业网络舆情数据集和企业客户数据集进行数据分析实验。实验结果表明,企业可以通过获取与其主营业务相关的网络舆情信息,实现客户满意度预测;同时,变尺度聚类算法结果能够为企业进一步制定销售战略和销售战术提供决策支持。
With the rapid development of social network platforms,public opinion has become a significant information source for enterprises to excavate valuable information and expand their competitive advantages.This paper studies the problem of enterprise customer relationship management under online public opinion.By constructing the information feedback model of enterprise customers,this paper describes the relationship among enterprise customer,social network user and enterprise public opinion.An algorithm of variable scale clustering based on the information feedback model is also proposed.The algorithm expands the solution of traditional clustering methods via transforming single scale analysis to multi-scale analysis,which overcomes the inconspicuous characteristics problem of clustering results in actual data application.This paper selects Weibo as data source,and implements data analysis experiments through an enterprise network public opinion data set and an enterprise customer data set.The experimental results show that enterprises can achieve customer satisfaction prediction by acquiring public opinion related to their main business.Also,the results of the variable-scale clustering algorithm can provide decision support for enterprises to further develop sales strategies and sales tactics.
作者
高学东
王艾
GAO Xue-dong;WANG Ai(Donlinks School of Economics and Management,BeijingUniversity of Science and Technology,Beijing 100083,China)
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2020年第7期232-239,共8页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71272161)。
关键词
企业网络舆情
客户满意度
情感分析
尺度变换
变尺度聚类
enterprise network public opinion
customer satisfaction
sentiment analysis
scale transformation
variable-scale clustering
