Listening to Users' Voice: Automatic Summarization of Helpful App Reviews
Cuiyun Gao, Yaoxian Li, Shuhan Qi, Yang Liu, Xuan Wang, Zibin Zheng,, Qing Liao

TL;DR
This paper introduces SOLAR, a framework that automatically summarizes helpful app reviews by predicting helpfulness, modeling topics and sentiments, and ranking reviews, thereby aiding developers in release planning.
Contribution
The paper presents a novel framework, SOLAR, which integrates helpfulness prediction, topic-sentiment modeling, and multi-factor ranking for review summarization, addressing limitations of prior methods.
Findings
SOLAR effectively summarizes helpful reviews for app release planning.
The framework outperforms baseline methods in review summarization accuracy.
Experiments on five popular apps demonstrate its practical utility.
Abstract
App reviews are crowdsourcing knowledge of user experience with the apps, providing valuable information for app release planning, such as major bugs to fix and important features to add. There exist prior explorations on app review mining for release planning, however, most of the studies strongly rely on pre-defined classes or manually-annotated reviews. Also, the new review characteristic, i.e., the number of users who rated the review as helpful, which can help capture important reviews, has not been considered previously. In the paper, we propose a novel framework, named SOLAR, aiming at accurately summarizing helpful user reviews to developers. The framework mainly contains three modules: The review helpfulness prediction module, topic-sentiment modeling module, and multi-factor ranking module. The review helpfulness prediction module assesses the helpfulness of reviews, i.e.,…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsSoftware Engineering Techniques and Practices · Software Engineering Research · Mobile and Web Applications
