MARC: A mobile application review classifier
Document Type
Conference Proceeding
Publication Date
1-1-2017
Abstract
Mobile application stores enable end-users of software to di- rectly express their needs and share their experience with mobile apps in the form of textual reviews. These reviews often contain important user feedback that can be leveraged by app developers to help them understand their end-user needs. However, such information are not readily available, and vetting individual reviews manually can be a tedious task. To alleviate this effort, we introduce MARC, a Mobile Application Review Classifier. MARC is a stand-alone automated solution that enables developers to extract and classify user reviews into fine-grained software maintenance requests, including bug reports and user requirements. MARC is equipped with a set of configuration features to enable practitioners and researchers to classify user reviews under di erent settings. A dataset of app reviews sampled from three apps are used to evaluate the performance of MARC. The results show that MARC achieves accuracy levels that can be adequate for practical and research applications.
Publication Source (Journal or Book title)
CEUR Workshop Proceedings
Recommended Citation
Jha, N., & Mahmoud, A. (2017). MARC: A mobile application review classifier. CEUR Workshop Proceedings, 1796 Retrieved from https://repository.lsu.edu/eecs_pubs/2593