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

Authors :
Wei, Jialiang
Courbis, Anne-Lise
Lambolais, Thomas
Xu, Binbin
Bernard, Pierre Louis
Dray, Gérard
Publication Year :
2022

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.<br />Comment: 7th National Conference on Practical Applications of Artificial Intelligence, 2022. Saint-\'Etienne, France. article in English and French, 4 pages each

Details

Language :
English
Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2206.14669
Document Type :
Working Paper
Full Text :
https://doi.org/10.5281/zenodo.7261877