同一款应用,不同国家:多数iOS应用下载用户评价研究

Kamonphop Srisopha, C. Phonsom, Keng-Nien Lin, B. Boehm
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引用次数: 6

摘要

之前关于手机应用评论的研究表明,用户评论包含大量信息,并被视为潜在的需求来源。然而,这一领域的大多数研究主要集中于挖掘和分析美国App Store的用户评论,而忽略了其他国家用户的评论。在本文中,我们试图通过分析用户评论来了解其他国家和美国用户对同一款应用的看法是否存在差异。在5个月的时间里,我们从9个英语国家检索了2018年下载量最高的15款iOS应用的300,643条用户评论,这些应用是由苹果直接发布的。我们手动地将3358个评论分为几个软件质量和改进因素。我们利用基于随机森林的算法来识别可用于区分美国和其他国家评论的因素。我们的初步结果表明,所有国家都有一些与美国比例不一致的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Same App, Different Countries: A Preliminary User Reviews Study on Most Downloaded iOS Apps
Prior work on mobile app reviews has demonstrated that user reviews contain a wealth of information and are seen as a potential source of requirements. However, most of the studies done in this area mainly focused on mining and analyzing user reviews from the US App Store, leaving reviews of users from other countries unexplored. In this paper, we seek to understand if the perception of the same apps between users from other countries and that from the US differs through analyzing user reviews. We retrieve 300,643 user reviews of the 15 most downloaded iOS apps of 2018, published directly by Apple, from nine English-speaking countries over the course of 5 months. We manually classify 3,358 reviews into several software quality and improvement factors. We leverage a random forest based algorithm to identify factors that can be used to differentiate reviews between the US and other countries. Our preliminary results show that all countries have some factors that are proportionally inconsistent with the US.
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