Albrecht Urs-Vito, Hasenfuß Gerd, von Jan Ute
Peter L Reichertz Institute for Medical Informatics, Hannover Medical School, Hannover, Germany.
Department of Cardiology and Pneumology, University Medical Center Göttingen, Göttingen, Germany.
JMIR Mhealth Uhealth. 2018 Nov 20;6(11):e11753. doi: 10.2196/11753.
In the app stores of mobile platforms, consumers are confronted with an enormous number of mobile apps. Over the past few years, considerable research has been undertaken into to identifying, characterizing, and evaluating apps, be it in health-related or other contexts. However, many of these projects are restricted to specific areas of application and offer little flexibility in adapting the applied criteria.
This paper presents an adaptable method for selecting and characterizing mobile apps listed in a mobile App Store (the Apple App Store). The method is based on filtering processes using predefined criteria, through a semiautomated retrospective App Store analysis (SARASA).
To illustrate the SARASA process, keyword-based filtering and metadata-based description, review, and ranking steps were applied to a dataset, more specifically, an April 2018 readout of the Medical category of the German App Store, with the aim of obtaining a list of cardiology-related apps.
From the original list of 39,427 apps within the "Medical" category of the App Store on April 14, 2018, 34,382 apps with store descriptions in languages other than German were removed. For the remaining 5045 apps, keywords related to cardiology were applied to filter the output, obtaining a final total of 335 subject-specific apps for further analysis and description.
SARASA provides an easy to use method for applying filtering processes to identify apps matching predefined, formal criteria from app stores. The criteria can be well adapted to the needs of users. Automatic and manual analyses are easily combined when using SARASA. In the future, additional features, such as algorithmic topic analyses, may supplement the process. Although the area of application is currently limited to Apple's App Store, expansion to other stores is planned. The method stands or falls with the transparency of the app store providers and the manufacturers to make relevant meta-information available. It is up to them to liberalize information and restrict censorship to provide clients, customers, and users truly fair circumstances finding their way around the app market.
在移动平台的应用商店中,消费者面临着大量的移动应用程序。在过去几年里,已经开展了大量研究来识别、描述和评估应用程序,无论是在健康相关领域还是其他背景下。然而,这些项目中的许多都局限于特定的应用领域,在调整应用标准方面缺乏灵活性。
本文提出一种适用于选择和描述移动应用商店(苹果应用商店)中列出的移动应用程序的方法。该方法基于使用预定义标准的过滤过程,通过半自动回顾性应用商店分析(SARASA)来实现。
为了说明SARASA过程,基于关键词的过滤以及基于元数据的描述、审查和排名步骤被应用于一个数据集,具体而言,是2018年4月德国应用商店医疗类别的数据读出,目的是获得一份与心脏病学相关的应用程序列表。
从2018年4月14日应用商店“医疗”类别中的39427个应用程序原始列表中,删除了34382个商店描述语言不是德语的应用程序。对于其余的5045个应用程序,应用与心脏病学相关的关键词来过滤输出,最终总共获得335个特定主题的应用程序用于进一步分析和描述。
SARASA提供了一种易于使用的方法,用于应用过滤过程来从应用商店中识别符合预定义正式标准的应用程序。这些标准可以很好地适应用户的需求。使用SARASA时,自动分析和手动分析很容易结合。未来,诸如算法主题分析等附加功能可能会补充该过程。虽然目前应用领域仅限于苹果应用商店,但计划扩展到其他商店。该方法的成败取决于应用商店提供商和制造商提供相关元信息的透明度。由他们来放宽信息并限制审查,以便为客户、顾客和用户提供在应用市场中找到出路的真正公平环境。