摘要
随着互联网的发展,网络口碑以用户评论真实客观的优点逐渐替代了传统的口碑,本文利用文本挖掘的方法研究用户满意度.首先,利用LDA模型建立用户满意度结构模型;然后,基于依存句法抽取语句情感标签,将HowNet情感词典与语义相似度算法相结合来识别语句情感倾向;最后,利用模糊综合评价法分析用户满意度.以摩拜为例,研究表明:从整体看,"摩拜"单车的用户满意度较高.但是,单车所需支付押金高、押金退还不及时,故障车多、软件定位精确度低等现象影响"摩拜"用户满意度的提升.
In this study,we use the method of textual emotion analysis to study the user satisfaction.First of all,we use the LDA model to establish the structure model of the user satisfaction.Then,the emotion tag of sentence is extracted based on dependency parsing technology,and the HowNet sentiment dictionary is combined with the semantic similarity algorithm to identify the sentiment tendency of the sentence.Finally,the fuzzy comprehensive evaluation method is used to study the user satisfaction.Taking Mobike for example,the research shows that the user satisfaction of Mobike bicycle is higher as a whole.However,the following phenomenon affects the improvement of customer satisfaction of Mobike,namely,required deposit is high,deposit refund is not timely,fault car is more,and the accuracy of positioning software is low.
作者
冒小栋
范涛
MAO Xiao-Dong;FAN Tao(School of Economics and Management, East China Jiaotong University, Nanchang 330013, China)
出处
《计算机系统应用》
2019年第1期222-227,共6页
Computer Systems & Applications
基金
江西省研究生创新(2017年)计划项目(YC2017-S264)~~
关键词
共享单车
用户满意度
LDA模型
依存句法分析
模糊综合评价
shared bicycle
textual emotion analysis
user satisfaction
fuzzy comprehensive evaluation
LDA model
