{"title":"Tool Support for Analyzing Mobile App Reviews","authors":"P. Vu, H. Pham, Tam The Nguyen, T. Nguyen","doi":"10.1109/ASE.2015.101","DOIUrl":null,"url":null,"abstract":"Mobile app reviews often contain useful user opinions for app developers. However, manual analysis of those reviews is challenging due to their large volume and noisynature. This paper introduces MARK, a supporting tool for review analysis of mobile apps. With MARK, an analyst can describe her interests of one or more apps via a set of keywords. MARK then lists the reviews most relevant to those keywords for further analyses. It can also draw the trends over time of the selected keywords, which might help the analyst to detect sudden changes in the related user reviews. To help the analyst describe her interests more effectively, MARK can automatically extract and rank the keywords by their associations with negative reviews, divide a large set of keywords into more cohesive subgroups, or expand a small set into a broader one.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"47 1","pages":"789-794"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASE.2015.101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
Mobile app reviews often contain useful user opinions for app developers. However, manual analysis of those reviews is challenging due to their large volume and noisynature. This paper introduces MARK, a supporting tool for review analysis of mobile apps. With MARK, an analyst can describe her interests of one or more apps via a set of keywords. MARK then lists the reviews most relevant to those keywords for further analyses. It can also draw the trends over time of the selected keywords, which might help the analyst to detect sudden changes in the related user reviews. To help the analyst describe her interests more effectively, MARK can automatically extract and rank the keywords by their associations with negative reviews, divide a large set of keywords into more cohesive subgroups, or expand a small set into a broader one.
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