Listening to Users' Voice: Automatic Summarization of Helpful App Reviews

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., whether the review is useful for developers. The topic-sentiment modeling module groups the topics of the helpful reviews and also predicts the associated sentiment, and the multi-factor ranking module aims at prioritizing semantically representative reviews for each topic as the review summary. Experiments on five popular apps indicate that SOLAR is effective for review summarization and promising for facilitating app release planning.