BACKGROUND
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.
OBJECTIVE
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).
METHODS
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.
RESULTS
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.
CONCLUSIONS
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.