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Dynamic aspect-based rating system and visualization

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Abstract

With an increasing number of product reviews available online, it has become impractical for potential customers to perceive all the available reviews in order to make an informed decision on their purchase. Product ratings that encapsulate product reviews swiftly and easily have become an alternative for customers. However, since several product ratings only display the overall rating, customers may still find it challenging to make an informed decision due to the lack of information between positive and negative reviews. In addition, existing product ratings are static in nature as they do not cater to customers’ different needs since they often prioritize different aspects of the product or product features. Accordingly, this paper proposes a dynamic aspect-based rating system accompanied by an aspect-based rating visualization to address the aforementioned problems. This rating system also considers the users’ reputations who have given product reviews to give a more holistic view of the users posting reviews. Moreover, our user study shows that our proposed rating visualization can be a competitive alternative in representing a product rating since it has the advantage of being informative and easily customized due to its ability to display rating scores based on users’ preferred aspects. In addition, the proposed visualization also enables customers to make more informed decisions since it displays a balance of both positive and negative reviews.

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Acknowledgements

The authors would like to thank the reviewers for their useful comments and suggestions. This research is partially supported by Research and Innovation grant from Institute of Technology Bandung. The views contained in this paper are those of the authors and should not be interpreted as representing the official policies of the sponsoring organisations or agencies.

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Maharani, W., Widyantoro, D.H. & Khodra, M.L. Dynamic aspect-based rating system and visualization. User Model User-Adap Inter 32, 1–24 (2022). https://doi.org/10.1007/s11257-021-09308-5

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