Product design opportunity identification through mining the critical minority of customer online reviews

Dong, Yanan; Wang, Yu; Zhang, Na

doi:10.1007/s10660-023-09683-8

Cited by 2 publications

(1 citation statement)

References 54 publications

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“…Hu et al [26] depicted aspects with polarity using a bubble chart in the domain of student teaching evaluations. Li et al [27] used a column chart to illustrate the number of opinions (positive and negative) for each aspect of customer reviews in the Chinese language. Most studies discussed used visual summaries, such as graphs and charts, to describe different aspects of the data.…”

Section: Introductionmentioning

confidence: 99%

Towards visual sentiment summary to understand customers’ satisfaction

Thanh Loan,

Tuan

2024

Bulletin EEI

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Due to the COVID-19 pandemic, the shopping behavior of customers has been significantly affected and is being shifted towards online shopping. Understanding the customers’ opinions, attitudes, and emotions in feedback and comments plays an essential role in making decisions for organizations and individuals (e.g., companies and customers). In this study, we propose sentiment summaries from the customer knowledgebase (SSoCK) framework that analyses customer feedback and improve a mechanism for sentiment summarization by using text analysis including sentiment analysis. In the experiments, various domains from customer reviews (e.g., computer and Canon) are used to conduct. The results show that the proposed SSoCK framework has the high performance of sentiment classification in terms of its accuracy when compared to the other approaches. Moreover, the proposed framework generates various kinds of sentiment summaries that can support managers/potential customers understand trending/interesting aspects of the product with customer satisfaction and can be easily updated with new reviews within the same domain without storing any original data.

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Section: Introductionmentioning

confidence: 99%