Online App Review Analysis for Identifying Emerging Issues

Abstract

Detecting emerging issues (e.g., new bugs) timely and precisely is crucial for developers to update their apps. App reviews provide an opportunity to proactively collect user complaints and promptly improve apps' user experience, in terms of bug fixing and feature refinement. However, the tremendous quantities of reviews and noise words (e.g., misspelled words) increase the difficulties in accurately identifying newly-appearing app issues. In this paper, we propose a novel and automated framework IDEA, which aims to IDentify Emerging App issues effectively based on online review analysis. We evaluate IDEA on six popular apps from Google Play and Apple's App Store, employing the official app changelogs as our ground truth. Experiment results demonstrate the effectiveness of IDEA in identifying emerging app issues. Feedback from engineers and product managers shows that 88.9% of them think that the identified issues can facilitate app development in practice. Moreover, we have successfully applied IDEA to several products of Tencent, which serve hundreds of millions of users.