Sentiment Analysis for the Customer Feedback in the Express Delivery Enterprise Evaluation System

Qi Wang, Shan Lu, Jin Lin, Cong Wang, Hongqiang Fan


Concomitant with rapid growth in recent years of Chinese e-commerce, an express delivery enterprise has developed and customer demand for express delivery services has increased. However, the Chinese express delivery industry has challenges such as low employee education level, sparse information availability, and high customer complaint rate. Big data technology provides a means for extracting customer opinions and studying customer behavior to realize greater overall customer satisfaction. In this study, the Chinese express delivery companies STO Express, YTO Express, ZTO Express, and YUNDA were selected as representatives and corresponding customer complaint information from the State Post Bureau analyzed. Sentiment analysis results indicate that companies can employ service decisions and develop measures to improve customer satisfaction and loyalty.


Chinese E-Commerce; Customer Feedback Information; Express Delivery Company; Logistics Industry; Sentiment Analysis; Service Evaluation

Full Text:


Included Database


Lee, S., Kim, W., 2017. Sentiment labeling for extending initial labeled data to improve semi-supervised sentiment classification. Electron. Commer. Res. Appl. 26, 35-49, ISSN 1567-4223, https://doi.org/10.1016/j.elerap.2017.09.006.

Ni, Z., Tao, Y., 2012. Research on the construction and evaluation of logistics service quality index. Logist Technol 31(19), 140–43.

Yan, H., 2016. Construction of evaluation index system of logistics service capability of express delivery enterprises. J Huainan Teach Coll 18(5), 39–44.

Zhou, Q., Xu, Z., Yen, N.Y., 2019. User sentiment analysis based on social network information and its application in consumer reconstruction intention. Comp Hum Behav 100, 177–83. https://doi.org/10.1016/j.chb.2018.07.006.

Zou, X., Yang, J., Zhang, J., 2018. Microblog sentiment analysis using social and topic context. PLoS ONE 13(2), e0191163. https://doi.org/10.1371/journal.pone.0191163.

DOI: https://doi.org/10.18282/l-e.v9i3.1574


  • There are currently no refbacks.