应用星球的崛起:对移动应用生态系统的系统研究

Thanasis Petsas, A. Papadogiannakis, M. Polychronakis, E. Markatos, T. Karagiannis
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引用次数: 111

摘要

由于移动技术的进步和移动用户数量的大量增加,移动应用程序(app)越来越受欢迎。因此,最近出现了一些应用程序分发平台,它们为现代移动设备上的软件应用程序的开发、下载和更新提供了一种新的方式。为了更好地了解这个快速发展的手机应用生态系统的下载模式、流行趋势和开发策略,我们系统地监测和分析了四个流行的第三方Android应用市场。我们的研究侧重于测量、分析和建模应用流行度分布,并探讨定价和收益策略如何影响应用流行度和开发商收入。我们的研究结果表明,与网络和点对点文件共享工作负载不同,应用程序受欢迎程度的分布偏离了通常观察到的zipf样模型。我们验证这些偏差可以主要归因于一个新的下载模式,我们称之为聚类效应。我们通过揭示用户下载量与应用类别的强烈时间相关性来验证这种效应的存在。基于这些观察结果,我们提出了一个新的应用下载分布的正式聚类模型,并证明它与测量数据非常吻合。此外,我们观察到付费应用遵循的流行分布与免费应用不同,并展示了基于广告的盈利策略的免费应用如何比付费应用产生更高的经济效益。我们相信,这项研究可以帮助应用商店设计师改进内容交付和推荐系统,也可以帮助应用开发者选择合适的定价政策来增加收入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rise of the planet of the apps: a systematic study of the mobile app ecosystem
Mobile applications (apps) have been gaining rising popularity due to the advances in mobile technologies and the large increase in the number of mobile users. Consequently, several app distribution platforms, which provide a new way for developing, downloading, and updating software applications in modern mobile devices, have recently emerged. To better understand the download patterns, popularity trends, and development strategies in this rapidly evolving mobile app ecosystem, we systematically monitored and analyzed four popular third-party Android app marketplaces. Our study focuses on measuring, analyzing, and modeling the app popularity distribution, and explores how pricing and revenue strategies affect app popularity and developers' income. Our results indicate that unlike web and peer-to-peer file sharing workloads, the app popularity distribution deviates from commonly observed Zipf-like models. We verify that these deviations can be mainly attributed to a new download pattern, to which we refer as the clustering effect. We validate the existence of this effect by revealing a strong temporal affinity of user downloads to app categories. Based on these observations, we propose a new formal clustering model for the distribution of app downloads, and demonstrate that it closely fits measured data. Moreover, we observe that paid apps follow a different popularity distribution than free apps, and show how free apps with an ad-based revenue strategy may result in higher financial benefits than paid apps. We believe that this study can be useful to appstore designers for improving content delivery and recommendation systems, as well as to app developers for selecting proper pricing policies to increase their income.
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