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Sentiment-aware Analysis of Mobile Apps User Reviews Regarding Particular Updates

Authors:
Xiaozhou Li
Zheying Zhang
Kostas Stefanidis

Keywords: mobile app; review; sentiment analysis; topic modeling; topic similarity

Abstract:
The contemporary online mobile application (app) market enables users to review the apps they use. These reviews are important assets reflecting the users’ needs and complaints regarding the particular apps, covering multiple aspects of the mobile apps quality. By investigating the content of such reviews, the app developers can acquire useful information guiding the future maintenance and evolution work. Furthermore, together with the updates of an app, the users’ reviews deliver particular complaints and praises regarding the particular updates. Despite that previous studies on opinion mining in mobile app reviews have provided various approaches in eliciting such critical information, limited studies focus on eliciting the user opinions regarding a particular mobile app update, or the impact the update imposes. Hence, this study proposes a systematic analysis method to elicit user opinions regarding a particular mobile app update by detecting the similar topics before and after this update, and validates this method via an experiment on an existing mobile app.

Pages: 99 to 107

Copyright: Copyright (c) IARIA, 2018

Publication date: October 14, 2018

Published in: conference

ISSN: 2308-4235

ISBN: 978-1-61208-668-2

Location: Nice, France

Dates: from October 14, 2018 to October 18, 2018