WCSE

A Customer Satisfaction Evaluation Method of the Power Company Using Sentiment Analysis

Abstract— This study proposes a method for improving customer satisfaction evaluation of power supply enterprises using sentiment analysis. First, a corpus of comments and posts about power supply enterprise is generated. Second, several machine learning algorithms are used to extract features from the corpus. Finally, the best classifier is used to evaluate the work of a company through the comments and reviews. The experiment shows that Multinomial naive Bayes is more appropriate for clustering the sentiment of Weibo posts. And this approach can benefit the power supply companies to improve their service.

Index Terms— customer satisfaction evaluation, sentiment analysis, power supply

WenHao Ou, BinBin Zhao
Power transformer engineering research institute, China Electric Power Research Institute, CHINA
Shi Shen
Key Laboratory of Environmental Change and Natural Disaster, Beijing Normal University, CHINA
Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University, CHINA
Wei Xia
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, CHINA
Gang Yang
State Grid Shanxi Electric Power Company, CHINA
LinJie Bai
State Grid Hebei Electric Power Company, CHINA
JianGuo Ma
State Grid Hubei Electric Power Company, CHINA

ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.17Xsrc="http://www.wcse.org/uploadfile/2019/0823/20190823055609629.png" style="width: 120px; height: 68px;" />[Download]

Cite: WenHao Ou, Shi Shen, Wei Xia, BinBin Zhao, Gang Yang, LinJie Bai, JianGuo Ma, "A Customer Satisfaction Evaluation Method of the Power Company Using Sentiment Analysis," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 1073-1077, Beijing, 25-27 June, 2017.