Understanding context of use from online customer reviews using BERT

Tong, Yanzhang, Liang, Yan, Liu, Ying ORCID: https://orcid.org/0000-0001-9319-5940, Spasic, Irena ORCID: https://orcid.org/0000-0002-8132-3885 and Hicks, Yulia ORCID: https://orcid.org/0000-0002-7179-4587 2022. Understanding context of use from online customer reviews using BERT. Presented at: IEEE 18th International Conference on Automation Science and Engineering (CASE 2022), Mexico City, Mexico, 20-24 August 2022. 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE). IEEE, 10.1109/CASE49997.2022.9926649

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Abstract

For user experience (UX) analysis in product design, the context of use (such as task, activities and environment) is a valuable element that enables context-awareness in accordance with the available context of use elements of users. Typically, conventional methods such as interviews or questionnaires are used to extract the context of use elements, but they are labour-intensive and time-consuming and thus do not scale well. On the other hand, the automatic extraction approaches from existing studies are not as effective as the extracted context of use phrases are not as informative. In this study, we present an automatic approach to exploit and understand the context of use elements from online customer reviews using BERT. Firstly, the context of use elements from online customer reviews is labelled using a BERT-based approach. Secondly, a syntactic-based post-processing is designed to check the labelled results and form the phrases related to the context of use. Finally, the customers’ preferences related to the contexts of use is analysed by studying and aggregating it with its relevant hedonic quality (such as positive or negative) which can then be used to enrich the UX modelling. For product designers, the modelling results can facilitate the optimisation of product design. A case study was conducted to understand and leverage the context of use elements in UX from online customer reviews to support customer strategy creation and design activities.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	IEEE
ISBN:	978-1-6654-9042-9
Date of First Compliant Deposit:	28 November 2022
Last Modified:	30 Nov 2022 07:56
URI:	https://orca.cardiff.ac.uk/id/eprint/150268

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