Aspect-based Kano categorization
作者：
Highlights：
• The aim of this paper is to derive a methodology for how to classify the extracted aspects from product reviews in terms of Kano categories (must-be, one-dimensional and attractive).
• The proposed methodology takes as a basis the general output of any aspect-based sentiment analysis method to provide a Kano categorization of the extracted aspects.
• Aspect frequency (AFi), sentiment (Oi+, Oi−) and Product Brand Dominance (PBDi) are the metrics used to categorize aspects.
• To determine if an aspect Ai is equally mentioned in the discussion of each identified product brand group, Product Brand Dominance (PBDi) measure is proposed.
• Results of the case study highlight the possibility for companies to identify relevant product features as input for the design process without the need to design (Kano) surveys.
摘要
•The aim of this paper is to derive a methodology for how to classify the extracted aspects from product reviews in terms of Kano categories (must-be, one-dimensional and attractive).•The proposed methodology takes as a basis the general output of any aspect-based sentiment analysis method to provide a Kano categorization of the extracted aspects.•Aspect frequency (AFi), sentiment (Oi+, Oi−) and Product Brand Dominance (PBDi) are the metrics used to categorize aspects.•To determine if an aspect Ai is equally mentioned in the discussion of each identified product brand group, Product Brand Dominance (PBDi) measure is proposed.•Results of the case study highlight the possibility for companies to identify relevant product features as input for the design process without the need to design (Kano) surveys.
论文关键词：Aspect,Categorization,Kano,Sentiment analysis (SA),Target setting
论文评审过程：Received 12 March 2018, Revised 25 October 2018, Accepted 8 November 2018, Available online 20 December 2018, Version of Record 20 December 2018.
论文官网地址：https://doi.org/10.1016/j.ijinfomgt.2018.11.004
