UISMiner: Mining UI suggestions from user reviews

摘要

GUI is an essential factor influencing users’ perception of an app. As the visual bridge between the user and the application, the quality of a GUI should be measured by the users’ subjective feelings. Therefore, to improve the UI, developers should pay attention to what users think and actively respond to their feedback. User reviews from different channels provide a way for developers to obtain users’ suggestions about the UI, and it could be of great benefit to improve the UI of their apps. Methods to mine different information (e.g., bug report, feature request) from reviews have been proposed in the previous works, however, suggestion information for supporting UI improvement has not gained much attention. In this paper, we propose UISMiner (UI Suggestion Miner), a novel approach to automatically mine the suggestions about the UI design from reviews. The application of UISMiner relies on natural language processing and machine learning classifier, which involves three main steps: 1) gaining reviews related to UI suggestion by training a classifier; 2) extracting UI suggestions from the obtained reviews by defining rules. 3) associating UI suggestions with the corresponding part in the UI. The experiment based on Google Play shows that UISMiner can effectively obtain reviews related to UI suggestions and extract such information from the gained reviews, the F-measure can reach 87.71% and 76.99% respectively. Furthermore, the survey on 10 developers shows that the information provided by us is useful for updating the UI of apps.