Title: Research on image of enterprise after-sales service based on text sentiment analysis

Authors: Yonghui Dai; Ying Wang; Bo Xu; Yingyi Wu; Jin Xian

Addresses: Management School, Shanghai University of International Business and Economics, Shanghai, 201620, China ' Management School, Shanghai University of International Business and Economics, Shanghai, 201620, China ' Management School, Shanghai University of International Business and Economics, Shanghai, 201620, China ' Department of Google Cloud Platform, Google Inc., Seattle, 98109, USA ' School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, 200433, China

Abstract: In recent years, the popularity of the internet has not only brought convenience to consumers, but also brought opportunities and challenges to enterprises. Among them, online reviews have a great impact on the enterprises, especially consumer reviews of the enterprises' after-sales service will affect the enterprises' image. In this paper, text sentiment analysis method is used for the analysis of after-sale online comments. According to the analysis results, enterprises can find the shortcomings of after-sales service and improve it. This paper provides the steps of the text sentiment analysis method, and uses the empirical data of the website to carry out the experiment. The results show that the method can effectively analyse the customer's sentiment and help the after-sales staff of the company to answer questions well, thereby improving the level of after-sales service and enterprise image.

Keywords: enterprise image; after-sale service; sentiment analysis; online comment.

DOI: 10.1504/IJCSE.2020.107367

International Journal of Computational Science and Engineering, 2020 Vol.22 No.2/3, pp.346 - 354

Received: 10 Dec 2019
Accepted: 19 Jan 2020
Published online: 18 May 2020 *

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