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

6000 French user reviews from three applications on Google Play (Garmin Connect, Huawei Health, Samsung Health) are labelled manually. We selected four labels: rating, bug report, feature request and user experience. Ratings are simple text which express the overall evaluation to that app, including praise, criticism, or dissuasion. Bug reports show the problems that users have met while using the app, like loss of data, crash of app, connection error, etc. Feature requests reflect the demande of users on new function, new content, new interface, etc. In user experience, users describe their experience in relation to the functionality of the app, how does certain functions be helpful. As we can observe from the following table, that shows examples of labelled user reviews, each review belongs to one or more categories. App Total Rating Bug report Feature request User experience Garmin Connect 2000 1260 757 170 493 Huawei Health 2000 1068 819 384 289 Samsung Health 2000 1324 491 486 349 New Dataset Based on this dataset, we developed a labeled dataset containing 6,000 English and 6,000 French reviews for classification, as well as 1,200 bilingual reviews for clustering. The new dataset has been made publicly available on Zenodo at the following link: https://zenodo.org/records/11066414