Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews

• URL: http://arxiv.org/abs/2206.14669v1
• Date: Wed, 29 Jun 2022 14:14:54 GMT
• Title: Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews
• Authors: Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais, Binbin Xu, Pierre Louis Bernard, G\'erard Dray
• Abstract summary: We provide an automated analysis using CamemBERT, which is a state-of-the-art language model in French. We created a multi-label classification dataset of 6000 user reviews from three applications in the Health & Fitness field. The results are encouraging and suggest that it's possible to identify automatically the reviews concerning requests for new features.
• Score: 0.440401067183266
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We are concerned by Data Driven Requirements Engineering, and in particular the consideration of user's reviews. These online reviews are a rich source of information for extracting new needs and improvement requests. In this work, we provide an automated analysis using CamemBERT, which is a state-of-the-art language model in French. We created a multi-label classification dataset of 6000 user reviews from three applications in the Health & Fitness field. The results are encouraging and suggest that it's possible to identify automatically the reviews concerning requests for new features. Dataset is available at: https://github.com/Jl-wei/APIA2022-French-user-reviews-classification-dataset.

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