Abstract
Product design experts depend on online customer reviews as a source of insight to improve product design. Previous works used aspect-based sentiment analysis to extract insight from product reviews. However, their approaches for requirements elicitation are less flexible than traditional tools such as interviews and surveys. They require costly data labeling or pre-labeled datasets, lack domain knowledge integration, and focus more on sentiment classification than flexible aspect-opinion analysis. Related works lack effective mechanisms for probing the customer feedback of complex configurable products. This study proposes a generic graph-based opinion mining and analysis method for product design improvement. First, a customer feedback data preprocessing and annotation pipeline that can incorporate designer-specified domain knowledge is proposed. Second, an intuitive opinion-aware labeled property graph data model is designed to ingest preprocessed feedback data and perform ad hoc opinion analysis. Applying the generic model to a real-world dataset demonstrates superior functionality and flexibility compared to related works. A wider range of analyses is supported in a single model without repeating data preprocessing and modeling. Specifically, the proposed method supports regular and comparative aspect-opinion analysis, aspect satisfaction/influence ranking, opinion trend extraction, and targeted aspect-opinion summarization.
Highlights
Customer feedback is a vital source of insight for product design improvements.User-centric product designers improve products by adapting product features to meet the requirements inherent in customer feedback
These kinds of capabilities are vital for analyzing the customer feedback of complex products
Businesses either have a global customer base or plan to build one for their products and services. Customers willingly express their opinions on products and services on a massive scale on online review platforms
Summary
Customer feedback is a vital source of insight for product design improvements. User-centric product designers improve products by adapting product features to meet the requirements inherent in customer feedback. The motivation of designers to satisfy customer requirements has never waned. They have relied on user-centric models such as the Kano [1], and QFD [2] for several decades to satisfy the Voice of Customer [3]. The process of product improvement increases in complexity if the product is configurable or multi-generational [4]. A component replacement or design change in such products affects related components. Choosing the correct features to improve helps manage risk and reduces the chance of product failure [5]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
