Understanding customer satisfaction via deep learning and natural language processing
作者：
Highlights：
• Deep learning is used to understand the factors that influence customer satisfaction.
• Customer surveys are analyzed using natural language processing.
• The drivers that determine customer experience are detected automatically.
• The data is cast into a multi-label classification problem.
• Experiments on 25,943 responses demonstrate the drivers can be identified accurately.
摘要
•Deep learning is used to understand the factors that influence customer satisfaction.•Customer surveys are analyzed using natural language processing.•The drivers that determine customer experience are detected automatically.•The data is cast into a multi-label classification problem.•Experiments on 25,943 responses demonstrate the drivers can be identified accurately.
论文关键词：Analytics,Customer satisfaction,Customer feedback,Natural language processing,Deep learning,BERT
论文评审过程：Received 22 October 2021, Revised 7 June 2022, Accepted 26 July 2022, Available online 30 July 2022, Version of Record 8 August 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118309
