Phrase-based extraction of user opinions in mobile app reviews

Phong Minh Vu, Hung Viet Pham, Tam The Nguyen, Tung Thanh Nguyen

Abstract

Mobile app reviews often contain useful user opinions like bug reports or suggestions. However, looking for those opinions manually in thousands of reviews is inefective and time- consuming. In this paper, we propose PUMA, an automated, phrase-based approach to extract user opinions in app reviews. Our approach includes a technique to extract phrases in reviews using part-of-speech (PoS) templates; a technique to cluster phrases having similar meanings (each cluster is considered as a major user opinion); and a technique to monitor phrase clusters with negative sentiments for their outbreaks over time. We used PUMA to study two popular apps and found that it can reveal severe problems of those apps reported in their user reviews.

BibTeX

@inproceedings{Vu-al:ASE16,
  author    = {Phong Minh Vu and
               Hung Viet Pham and
               Tam The Nguyen and
               Tung Thanh Nguyen},
  title     = {Phrase-based extraction of user opinions in mobile app reviews},
  booktitle = {ASE},
  pages     = {726--731},
  publisher = {{ACM}},
  year      = {2016},
}

Phrase-based extraction of user opinions in mobile app reviews

Abstract

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