Analysis of sentiment expressions for user-centered design
作者：
Highlights：
• We translate online customer reviews into attribute-level design insights.
• We develop a methodology for attribute-sentiment expression mapping.
• The algorithms developed utilize NLTK, Word2Vec and Stanford Parser.
• We build on sentiment analysis and information extraction methods.
• We identify customer segments based on the individual reviews analyzed.
摘要
•We translate online customer reviews into attribute-level design insights.•We develop a methodology for attribute-sentiment expression mapping.•The algorithms developed utilize NLTK, Word2Vec and Stanford Parser.•We build on sentiment analysis and information extraction methods.•We identify customer segments based on the individual reviews analyzed.
论文关键词：Sentiment analysis,Information extraction,Natural language processing,User-centered design
论文评审过程：Received 21 November 2019, Revised 8 January 2021, Accepted 11 January 2021, Available online 15 January 2021, Version of Record 29 January 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114604
